
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler,MinMaxScaler
from sklearn.inspection import permutation_importance
from sklearn.naive_bayes import GaussianNB
from sklearn.metrics import classification_report, confusion_matrix, roc_curve, auc
from imblearn.over_sampling import RandomOverSampler
import keras.backend as K
import os
import pydotplus
from tensorflow.keras.layers import Lambda
import tensorflow_addons as tfa
import pandas as pd
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.multiclass import OneVsRestClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split 
from sklearn import metrics
import imblearn
import warnings
from collections import Counter
from imblearn.over_sampling import SMOTE
from collections import Counter
from matplotlib import pyplot
from sklearn.preprocessing import LabelEncoder
from sklearn.tree import export_graphviz
from six import StringIO
from PIL import Image
from imblearn.over_sampling import SMOTE
from collections import Counter
from matplotlib import pyplot
# import pydotplus
from numpy import mean
import os
from PIL import  Image
import seaborn as sns#visualization
import itertools
import warnings
import lightgbm as lgb
from sklearn.model_selection import KFold, StratifiedKFold
from sklearn.metrics import roc_auc_score
from sklearn.manifold import TSNE
from sklearn.decomposition import PCA
import io
from sklearn.neural_network import MLPClassifier
import plotly.offline as py#visualization
import plotly.graph_objs as go#visualization
import plotly.tools as tls#visualization
import plotly.figure_factory as ff#visualization
import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import mean_squared_error,roc_auc_score,precision_score
from itertools import cycle
from sklearn import svm, datasets
from sklearn.metrics import roc_curve, auc
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import label_binarize
from sklearn.multiclass import OneVsRestClassifier
from scipy import interp
from sklearn.metrics import roc_auc_score
from numpy import std
import lightgbm as lgb
from sklearn.preprocessing import PowerTransformer
from sklearn import svm, datasets
from pandas import read_csv
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import RepeatedStratifiedKFold
import IPython.display as display
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier
py.init_notebook_mode(connected=True)
warnings.filterwarnings("ignore")
%matplotlib inline

Using TensorFlow backend.


data_0 = pd.read_csv('final2.csv')
data_0=data_0.dropna()
data_0 = data_0.iloc[: , 1:]
data_0=data_0.drop(['BIRTH','SCREEN',"HALLUC","BIRTH","METHADONE","OTHERDRUGS"],axis=1)


#labels
lab = data_0["DAST"].value_counts().keys().tolist()
#values
val = data_0["DAST"].value_counts().values.tolist()

trace = go.Pie(labels = lab ,
               values = val ,
               marker = dict(colors =  [ 'royalblue' ,'lime'],
                             line = dict(color = "white",
                                         width =  1.3)
                            ),
               rotation = 90,
               hoverinfo = "label+value+text",
               hole = .5
              )
layout = go.Layout(dict(title = "class imbalance",
                        plot_bgcolor  = "rgb(243,243,243)",
                        paper_bgcolor = "rgb(243,243,243)",
                       )
                  )

data1 = [trace]
fig = go.Figure(data = data1,layout = layout)
py.iplot(fig)


df=data_0.copy()


# df=df.sample(frac=1).head()
df


df['DAST'] = df['DAST'].astype(float).astype(int)
df['SEX'] = df['SEX'].astype(float).astype(int)
df['HISPANIC'] = df['HISPANIC'].astype(float).astype(int)
df['RACE'] = df['RACE'].astype(float).astype(int)
df['VET'] = df['VET'].astype(float).astype(int)
df['ACTIVE'] = df['ACTIVE'].astype(float).astype(int)
df['DEPLOY'] = df['DEPLOY'].astype(float).astype(int)
df['AUDIT'] = df['AUDIT'].astype(float).astype(int)
df['COSCREEN'] = df['COSCREEN'].astype(float).astype(int)
df['RT'] = df['RT'].astype(float).astype(int)
df['BI'] = df['BI'].astype(float).astype(int)
df['BT'] = df['BT'].astype(float).astype(int)
df['INJECT'] = df['INJECT'].astype(float).astype(int)
df['TOBMONTH'] = df['TOBMONTH'].astype(float).astype(int)
###############################################################
df['ANYALC'] = df['ANYALC'].astype(float).astype(int)
df['BINGEDAYS'] = df['BINGEDAYS'].astype(float).astype(int)
df['DRUGDAYS'] = df['DRUGDAYS'].astype(float).astype(int)
df['ALCDRUGS'] = df['ALCDRUGS'].astype(float).astype(int)
df['DAYSCOCAINE'] = df['DAYSCOCAINE'].astype(float).astype(int)
df['MARYJDAYS'] = df['MARYJDAYS'].astype(float).astype(int)
df['ANYOPIATEDAYS'] = df['ANYOPIATEDAYS'].astype(float).astype(int)
df['METHDAYS'] = df['METHDAYS'].astype(float).astype(int)
df['AGE'] = df['AGE'].astype(float).astype(int)
df


def aply_oonehot(df, col):
    df_en = pd.get_dummies(df[col])
    
    df_en = df_en.drop(df_en.columns[0], 1)
    
    cols = [str(col)+'_'+str(c) for c in df_en.columns]
    df_en.columns = cols
    
    df = df.drop(col, 1)
    
    
    df = pd.concat([df, df_en], axis=1)
    return df


train,test=train_test_split(df, test_size=.25)
# pt = PowerTransformer()
# pt.fit(df)
# train=pt.transform(train)
# train=pd.DataFrame(train,columns=['DAST', 'SEX', 'HISPANIC', 'RACE', 'VET', 'ACTIVE', 'DEPLOY', 'AUDIT',
#        'COSCREEN', 'BI', 'BT', 'RT', 'ANYALC', 'BINGEDAYS', 'DRUGDAYS',
#        'ALCDRUGS', 'DAYSCOCAINE', 'MARYJDAYS', 'ANYOPIATEDAYS', 'METHDAYS',
#        'INJECT', 'AGE', 'TOBMONTH'])


train = aply_oonehot(train, 'COSCREEN')
test =  aply_oonehot(test, 'COSCREEN')

train = aply_oonehot(train, 'SEX')
test =  aply_oonehot(test, 'SEX')

train = aply_oonehot(train, 'HISPANIC')
test =  aply_oonehot(test, 'HISPANIC')
      
train = aply_oonehot(train, 'RACE')
test =  aply_oonehot(test, 'RACE')

train = aply_oonehot(train, 'VET')
test =  aply_oonehot(test, 'VET')

train = aply_oonehot(train, 'ACTIVE')
test =  aply_oonehot(test, 'ACTIVE')      


train = aply_oonehot(train, 'DEPLOY')
test =  aply_oonehot(test, 'DEPLOY')   

train = aply_oonehot(train, 'AUDIT')
test =  aply_oonehot(test, 'AUDIT')   


train = aply_oonehot(train, 'BI')
test =  aply_oonehot(test, 'BI')   

train = aply_oonehot(train, 'BT')
test =  aply_oonehot(test, 'BT')   

train = aply_oonehot(train, 'RT')
test =  aply_oonehot(test, 'RT')   

train = aply_oonehot(train, 'INJECT')
test =  aply_oonehot(test, 'INJECT')   

train = aply_oonehot(train, 'TOBMONTH')
test =  aply_oonehot(test, 'TOBMONTH') 

print (train.columns)

Index(['DAST', 'ANYALC', 'BINGEDAYS', 'DRUGDAYS', 'ALCDRUGS', 'DAYSCOCAINE',
       'MARYJDAYS', 'ANYOPIATEDAYS', 'METHDAYS', 'AGE', 'COSCREEN_1', 'SEX_1',
       'SEX_2', 'HISPANIC_1', 'RACE_2', 'RACE_3', 'VET_1', 'ACTIVE_1',
       'DEPLOY_1', 'DEPLOY_2', 'DEPLOY_3', 'DEPLOY_4', 'DEPLOY_5', 'AUDIT_1',
       'AUDIT_2', 'BI_1', 'BT_1', 'RT_1', 'INJECT_1', 'TOBMONTH_1'],
      dtype='object')


XX_train, XX_val = train_test_split(train, test_size=900)

cols = [c for c in train.columns if c not in ['DAST']]

X_train = MinMaxScaler().fit_transform(XX_train[cols])
y_train = XX_train['DAST'].to_numpy()

X_test = MinMaxScaler().fit_transform(XX_val[cols])
y_test= XX_val['DAST'].to_numpy()

strategy = {0:6000, 1:6000,2:6000,3:6000,4:6000}
oversample = RandomOverSampler(sampling_strategy='minority')
X_train, y_train = oversample.fit_resample(X_train, y_train)
oversample = SMOTE(sampling_strategy=strategy,k_neighbors=2)
X_train, y_train = oversample.fit_resample(X_train, y_train)
X_train.shape
print (train.columns.str.strip())

Index(['DAST', 'ANYALC', 'BINGEDAYS', 'DRUGDAYS', 'ALCDRUGS', 'DAYSCOCAINE',
       'MARYJDAYS', 'ANYOPIATEDAYS', 'METHDAYS', 'AGE', 'COSCREEN_1', 'SEX_1',
       'SEX_2', 'HISPANIC_1', 'RACE_2', 'RACE_3', 'VET_1', 'ACTIVE_1',
       'DEPLOY_1', 'DEPLOY_2', 'DEPLOY_3', 'DEPLOY_4', 'DEPLOY_5', 'AUDIT_1',
       'AUDIT_2', 'BI_1', 'BT_1', 'RT_1', 'INJECT_1', 'TOBMONTH_1'],
      dtype='object')


counter = Counter(y_train)
for k,v in counter.items():
	per = v / len(y_train) * 100
	print('Class=%d, n=%d (%.3f%%)' % (k, v, per))
# plot the distribution
pyplot.bar(counter.keys(), counter.values())
pyplot.show()

Class=0, n=6000 (20.000%)
Class=1, n=6000 (20.000%)
Class=3, n=6000 (20.000%)
Class=2, n=6000 (20.000%)
Class=4, n=6000 (20.000%)


from sklearn.metrics import confusion_matrix
from sklearn.metrics import classification_report
from sklearn.metrics import cohen_kappa_score
from sklearn.metrics import accuracy_score, log_loss

def print_stats(ytest, ypred):
    
    print("Accuracy: {:.5f}, Cohen's Kappa Score: {:.5f}".format(
        accuracy_score(ytest, ypred), 
        cohen_kappa_score(ytest, ypred, weights="quadratic")))
    print("Confusion Matrix:")
    print(confusion_matrix(ytest, ypred))
    print("Classification Report:")
    print(classification_report(ytest, ypred))


clf=DecisionTreeClassifier(max_depth=7,criterion='gini', random_state = 42)
# evaluate a model
def evaluate_model(X, y, model):
	# define evaluation procedure
	cv = RepeatedStratifiedKFold(n_splits=5, n_repeats=3, random_state=1)
	# evaluate model
	scores = cross_val_score(model, X, y, scoring='accuracy', cv=cv, n_jobs=-1)
	return scores

clf.fit(X_train,y_train)
scores = evaluate_model(X_train, y_train,clf)
# summarize performance
print('Cross_validation_Mean Accuracy: %.3f (%.3f)' % (mean(scores), std(scores)))

Cross_validation_Mean Accuracy: 0.998 (0.001)


print('R^2 Training Score: {:.2f} \nR^2 Validation Score: {:.2f}'.format(clf.score(X_train, y_train),
                                                                         clf.score(X_test, y_test)))

R^2 Training Score: 1.00 
R^2 Validation Score: 0.99


from sklearn.base import clone 

def imp_df(column_names, importances):
    data = {
        'Feature': column_names,
        'Importance': importances,
    }
    df = pd.DataFrame(data) \
        .set_index('Feature') \
        .sort_values('Importance', ascending=False)

    return df


def drop_col_feat_imp(model, X_train, y_train, random_state = 42):
    
    # clone the model to have the exact same specification as the one initially trained
    model_clone = clone(model)
    # set random_state for comparability
    model_clone.random_state = random_state
    # training and scoring the benchmark model
    model_clone.fit(X_train, y_train)
    benchmark_score = model_clone.score(X_train, y_train)
    # list for storing feature importances
    importances = []
    
    # iterating over all columns and storing feature importance (difference between benchmark and new model)
    for col in X_train.columns:
        model_clone = clone(model)
        model_clone.random_state = random_state
        model_clone.fit(X_train.drop(col, axis = 1), y_train)
        drop_col_score = model_clone.score(X_train.drop(col, axis = 1), y_train)
        importances.append(benchmark_score - drop_col_score)
    
    importances_df = imp_df(X_train.columns, importances)
    return importances_df

drop_col_feat_imp(clf, pd.DataFrame(X_train), y_train)


importance = permutation_importance(clf, X_train, y_train, random_state = 42)
importance =importance.importances_mean
plt.figure(figsize=(20,10))
importance = (importance-min(importance))/(max(importance)-min(importance))*100
for i,v in enumerate(importance):
    
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 0.01483
Feature: 1, Score: 0.01271
Feature: 2, Score: 3.01637
Feature: 3, Score: 1.14385
Feature: 4, Score: 0.00000
Feature: 5, Score: 0.00000
Feature: 6, Score: 0.00000
Feature: 7, Score: 0.00000
Feature: 8, Score: 1.21163
Feature: 9, Score: 75.61906
Feature: 10, Score: 0.51473
Feature: 11, Score: 0.00000
Feature: 12, Score: 0.28384
Feature: 13, Score: 31.41986
Feature: 14, Score: 0.00000
Feature: 15, Score: 10.01716
Feature: 16, Score: 0.00000
Feature: 17, Score: 0.00000
Feature: 18, Score: 0.83459
Feature: 19, Score: 0.06778
Feature: 20, Score: 0.00000
Feature: 21, Score: 0.00000
Feature: 22, Score: 1.97844
Feature: 23, Score: 14.29812
Feature: 24, Score: 100.00000
Feature: 25, Score: 71.50967
Feature: 26, Score: 89.08683
Feature: 27, Score: 0.00000
Feature: 28, Score: 0.47237


y_pred = clf.predict(X_test)

# Model Accuracy, how often is the classifier correct?
print('Criterion=Gini',metrics.accuracy_score(y_test, y_pred))

Criterion=Gini 0.9877777777777778


# Binarize the output
y_train = label_binarize(y_train, classes=[0, 1, 2,3,4])
n_classes = y_train.shape[1]
y_test = label_binarize(y_test, classes=[0, 1, 2,3,4])

y_score = clf.fit(X_train, y_train).predict(X_test)
fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.98778, Cohen's Kappa Score: 0.91688
Confusion Matrix:
[[823   1   2   1   0]
 [  2  60   0   0   0]
 [  0   0   4   1   0]
 [  0   0   0   2   3]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      1.00      1.00       827
           1       0.98      0.97      0.98        62
           2       0.67      0.80      0.73         5
           3       0.40      0.40      0.40         5
           4       0.00      0.00      0.00         1

    accuracy                           0.99       900
   macro avg       0.61      0.63      0.62       900
weighted avg       0.99      0.99      0.99       900


df_k=train.drop(['DAST'],axis=1)
all_feat=df_k.columns                                                                                          
# all_feat=df_k.columns
print(all_feat)
importance = pd.DataFrame(clf.feature_importances_,
                                   index = df_k.columns,
                                    columns=['importance']).sort_values('importance', 
                                                                        ascending=False)


importances = clf.feature_importances_
pyplot.bar(range(len(clf.feature_importances_)), clf.feature_importances_)
pyplot.show()

Index(['ANYALC', 'BINGEDAYS', 'DRUGDAYS', 'ALCDRUGS', 'DAYSCOCAINE',
       'MARYJDAYS', 'ANYOPIATEDAYS', 'METHDAYS', 'AGE', 'COSCREEN_1', 'SEX_1',
       'SEX_2', 'HISPANIC_1', 'RACE_2', 'RACE_3', 'VET_1', 'ACTIVE_1',
       'DEPLOY_1', 'DEPLOY_2', 'DEPLOY_3', 'DEPLOY_4', 'DEPLOY_5', 'AUDIT_1',
       'AUDIT_2', 'BI_1', 'BT_1', 'RT_1', 'INJECT_1', 'TOBMONTH_1'],
      dtype='object')


dot_data = StringIO()
export_graphviz(clf, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True,feature_names = cols,class_names=['0','1','2','3','4'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
graph.write_png('images/case-1/DT-DAST-GINI.png')
img0 = Image.open('images/case-1/DT-DAST-GINI.png')
display.display(img0)


import lime.lime_tabular
classes=[0, 1, 2, 3, 4]
df_k=df.drop(['DAST'],axis=1)
all_feat=train.columns
print(all_feat)
model = clf
model.fit(X_train, y_train.argmax(axis=1))
predict_fn_xgb = lambda x: model.predict_proba(x).astype(float)
explainer = lime.lime_tabular.LimeTabularExplainer(X_train,mode='classification',feature_selection= 'auto',
                                                   class_names=classes,feature_names = all_feat, 
                                                   kernel_width=None,discretize_continuous=True)

Index(['DAST', 'ANYALC', 'BINGEDAYS', 'DRUGDAYS', 'ALCDRUGS', 'DAYSCOCAINE',
       'MARYJDAYS', 'ANYOPIATEDAYS', 'METHDAYS', 'AGE', 'COSCREEN_1', 'SEX_1',
       'SEX_2', 'HISPANIC_1', 'RACE_2', 'RACE_3', 'VET_1', 'ACTIVE_1',
       'DEPLOY_1', 'DEPLOY_2', 'DEPLOY_3', 'DEPLOY_4', 'DEPLOY_5', 'AUDIT_1',
       'AUDIT_2', 'BI_1', 'BT_1', 'RT_1', 'INJECT_1', 'TOBMONTH_1'],
      dtype='object')


explanation = explainer.explain_instance(X_test[32], predict_fn_xgb, num_features=25,top_labels=5)

explanation.show_in_notebook()


dtree = DecisionTreeClassifier(criterion='entropy', max_depth=7)
dtree.fit(X_train, y_train)
pred = dtree.predict(X_test)
print('Criterion=entropy', metrics.accuracy_score(y_test, pred))

Criterion=entropy 0.9777777777777777


importance = permutation_importance(dtree, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 4.59184
Feature: 1, Score: 2.55102
Feature: 2, Score: 5.10204
Feature: 3, Score: 4.25170
Feature: 4, Score: 2.55102
Feature: 5, Score: 2.55102
Feature: 6, Score: 2.55102
Feature: 7, Score: 2.55102
Feature: 8, Score: 2.55102
Feature: 9, Score: 0.00000
Feature: 10, Score: 1.87075
Feature: 11, Score: 2.55102
Feature: 12, Score: 2.55102
Feature: 13, Score: 1.02041
Feature: 14, Score: 2.55102
Feature: 15, Score: 2.55102
Feature: 16, Score: 2.55102
Feature: 17, Score: 2.55102
Feature: 18, Score: 2.55102
Feature: 19, Score: 2.55102
Feature: 20, Score: 2.55102
Feature: 21, Score: 2.55102
Feature: 22, Score: 9.86395
Feature: 23, Score: 6.80272
Feature: 24, Score: 100.00000
Feature: 25, Score: 15.30612
Feature: 26, Score: 10.20408
Feature: 27, Score: 2.55102
Feature: 28, Score: 2.55102


y_score = dtree.fit(X_train, y_train).predict(X_test)
fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.97778, Cohen's Kappa Score: 0.88386
Confusion Matrix:
[[814  11   0   2   0]
 [  2  60   0   0   0]
 [  0   0   4   1   0]
 [  0   0   0   2   3]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      0.98      0.99       827
           1       0.85      0.97      0.90        62
           2       1.00      0.80      0.89         5
           3       0.33      0.40      0.36         5
           4       0.00      0.00      0.00         1

    accuracy                           0.98       900
   macro avg       0.64      0.63      0.63       900
weighted avg       0.98      0.98      0.98       900


dot_data = StringIO()
export_graphviz(dtree, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True,feature_names = cols,class_names=['0','1','2','3','4'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
graph.write_png('images/case-1/DT-DAST-ENTROPY.png')
img0 = Image.open('images/case-1/DT-DAST-ENTROPY.png')

display.display(img0)


max_depth = []
acc_gini = []
acc_entropy = []
for i in range(1,30):
 dtree2 = DecisionTreeClassifier(criterion='gini', max_depth=i)
 dtree2.fit(X_train, y_train)
 pred = dtree2.predict(X_test)
 acc_gini.append(metrics.accuracy_score(y_test, pred))
 ####
 dtree3 = DecisionTreeClassifier(criterion='entropy', max_depth=i)
 dtree3.fit(X_train, y_train)
 pred = dtree3.predict(X_test)
 acc_entropy.append(metrics.accuracy_score(y_test, pred))
 ####
 max_depth.append(i)
d = pd.DataFrame({'acc_gini':pd.Series(acc_gini), 
 'acc_entropy':pd.Series(acc_entropy),
 'max_depth':pd.Series(max_depth)})
# visualizing changes in parameters
plt.plot('max_depth','acc_gini', data=d, label='gini')
plt.plot('max_depth','acc_entropy', data=d, label='entropy')
plt.xlabel('max_depth')
plt.ylabel('accuracy')
plt.legend()

<matplotlib.legend.Legend at 0x7f565ca5ba60>


clf_pruned = DecisionTreeClassifier(criterion = "gini", random_state = 500,
                               max_depth=3, min_samples_leaf=7)
clf_pruned.fit(X_train, y_train)
pred = clf_pruned.predict(X_test)
print('Pruned', metrics.accuracy_score(y_test, pred))

Pruned 0.9822222222222222


importance = permutation_importance(clf_pruned, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 0.00000
Feature: 1, Score: 0.00000
Feature: 2, Score: 9.63665
Feature: 3, Score: 0.00000
Feature: 4, Score: 0.00000
Feature: 5, Score: 0.00000
Feature: 6, Score: 0.00000
Feature: 7, Score: 0.00000
Feature: 8, Score: 0.00000
Feature: 9, Score: 6.31912
Feature: 10, Score: 0.00000
Feature: 11, Score: 0.00000
Feature: 12, Score: 0.00000
Feature: 13, Score: 0.00000
Feature: 14, Score: 0.00000
Feature: 15, Score: 0.00000
Feature: 16, Score: 0.00000
Feature: 17, Score: 0.00000
Feature: 18, Score: 0.00000
Feature: 19, Score: 0.00000
Feature: 20, Score: 0.00000
Feature: 21, Score: 0.00000
Feature: 22, Score: 16.11374
Feature: 23, Score: 0.00000
Feature: 24, Score: 100.00000
Feature: 25, Score: 0.78989
Feature: 26, Score: 6.63507
Feature: 27, Score: 0.00000
Feature: 28, Score: 0.00000


y_score = clf_pruned.fit(X_train, y_train).predict(X_test)
fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.98222, Cohen's Kappa Score: 0.82736
Confusion Matrix:
[[824   0   1   1   1]
 [  4  58   0   0   0]
 [  3   0   1   0   1]
 [  0   0   0   1   4]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       0.99      1.00      0.99       827
           1       1.00      0.94      0.97        62
           2       0.50      0.20      0.29         5
           3       0.33      0.20      0.25         5
           4       0.00      0.00      0.00         1

    accuracy                           0.98       900
   macro avg       0.56      0.47      0.50       900
weighted avg       0.98      0.98      0.98       900


dot_data = StringIO()
export_graphviz(clf_pruned, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True,feature_names = cols,class_names=['0','1','2','3','4'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
graph.write_png('images/case-1/DT-Pruned-DAST.png')
img0 = Image.open('images/case-1/DT-Pruned-DAST.png')

display.display(img0)


rf_gini = RandomForestClassifier(criterion='gini', max_depth= 7,n_estimators = 100,
                           n_jobs = -1,
                           oob_score = True,
                           bootstrap = True,
                           random_state = 42)
rf_gini.fit(X_train, y_train)
pred = rf_gini.predict(X_test)
print('Criterion=gini', metrics.accuracy_score(y_test, pred))

Criterion=gini 0.9733333333333334


importance = permutation_importance(rf_gini, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 3.04114
Feature: 1, Score: 3.75671
Feature: 2, Score: 6.26118
Feature: 3, Score: 1.07335
Feature: 4, Score: 1.07335
Feature: 5, Score: 3.75671
Feature: 6, Score: 1.07335
Feature: 7, Score: 1.07335
Feature: 8, Score: 3.57782
Feature: 9, Score: 2.86225
Feature: 10, Score: 0.00000
Feature: 11, Score: 1.07335
Feature: 12, Score: 0.71556
Feature: 13, Score: 1.96780
Feature: 14, Score: 1.07335
Feature: 15, Score: 3.04114
Feature: 16, Score: 1.07335
Feature: 17, Score: 0.89445
Feature: 18, Score: 1.07335
Feature: 19, Score: 1.07335
Feature: 20, Score: 1.07335
Feature: 21, Score: 1.07335
Feature: 22, Score: 8.94454
Feature: 23, Score: 2.86225
Feature: 24, Score: 100.00000
Feature: 25, Score: 7.33453
Feature: 26, Score: 6.97674
Feature: 27, Score: 1.07335
Feature: 28, Score: 2.14669


y_score = rf_gini.fit(X_train, y_train).predict(X_test)
fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.97778, Cohen's Kappa Score: 0.83594
Confusion Matrix:
[[817  10   0   0   0]
 [  3  59   0   0   0]
 [  2   0   3   0   0]
 [  2   0   0   1   2]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       0.99      0.99      0.99       827
           1       0.86      0.95      0.90        62
           2       1.00      0.60      0.75         5
           3       0.50      0.20      0.29         5
           4       0.00      0.00      0.00         1

    accuracy                           0.98       900
   macro avg       0.67      0.55      0.59       900
weighted avg       0.98      0.98      0.98       900


estimator =rf_gini.estimators_[5]
dot_data = StringIO()
export_graphviz(estimator, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True,feature_names = cols,class_names=['0','1','2','3','4'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
graph.write_png('images/case-1/RF-DAST-GINI.png')
img0 = Image.open('images/case-1/RF-DAST-GINI.png')

display.display(img0)


rf_entropy = RandomForestClassifier(criterion='entropy', max_depth= 7,n_estimators = 100,
                           n_jobs = -1,
                           oob_score = True,
                           bootstrap = True,
                           random_state = 42)
rf_entropy.fit(X_train, y_train)
pred = rf_entropy.predict(X_test)
print('Criterion=entropy', metrics.accuracy_score(y_test, pred))

Criterion=entropy 0.9755555555555555


importance = permutation_importance(rf_entropy, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 1.89983
Feature: 1, Score: 2.93610
Feature: 2, Score: 5.87219
Feature: 3, Score: 1.38169
Feature: 4, Score: 0.51813
Feature: 5, Score: 4.49050
Feature: 6, Score: 0.51813
Feature: 7, Score: 0.51813
Feature: 8, Score: 1.72712
Feature: 9, Score: 0.00000
Feature: 10, Score: 1.38169
Feature: 11, Score: 0.51813
Feature: 12, Score: 0.51813
Feature: 13, Score: 0.69085
Feature: 14, Score: 0.51813
Feature: 15, Score: 1.89983
Feature: 16, Score: 0.51813
Feature: 17, Score: 0.51813
Feature: 18, Score: 0.51813
Feature: 19, Score: 0.51813
Feature: 20, Score: 1.38169
Feature: 21, Score: 0.51813
Feature: 22, Score: 8.98100
Feature: 23, Score: 2.24525
Feature: 24, Score: 100.00000
Feature: 25, Score: 9.32642
Feature: 26, Score: 7.08117
Feature: 27, Score: 0.51813
Feature: 28, Score: 1.38169


y_score =rf_entropy.fit(X_train, y_train).predict(X_test)
fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.98000, Cohen's Kappa Score: 0.87444
Confusion Matrix:
[[818   9   0   0   0]
 [  2  59   1   0   0]
 [  0   0   4   1   0]
 [  2   0   0   1   2]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      0.99      0.99       827
           1       0.87      0.95      0.91        62
           2       0.80      0.80      0.80         5
           3       0.33      0.20      0.25         5
           4       0.00      0.00      0.00         1

    accuracy                           0.98       900
   macro avg       0.60      0.59      0.59       900
weighted avg       0.98      0.98      0.98       900


estimator = rf_entropy.estimators_[5]
dot_data = StringIO()
export_graphviz(estimator, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True,feature_names = cols,class_names=['0','1','2','3','4'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
graph.write_png('images/case-1/RF-DAST-ENTROPY.png')
img0 = Image.open('images/case-1/RF-DAST-ENTROPY.png')

display.display(img0)


max_depth = []
acc_gini = []
acc_entropy = []
for i in range(1,30):
 rf_gini1 = RandomForestClassifier(criterion='gini', max_depth= i)
 rf_gini1.fit(X_train, y_train)
 pred = rf_gini1.predict(X_test)
 acc_gini.append(metrics.accuracy_score(y_test, pred))
 ####
 rf_entropy1 =  RandomForestClassifier(criterion='entropy', max_depth= i)
 rf_entropy1.fit(X_train, y_train)
 pred = rf_entropy1.predict(X_test)
 acc_entropy.append(metrics.accuracy_score(y_test, pred))
 ####
 max_depth.append(i)
d = pd.DataFrame({'acc_gini':pd.Series(acc_gini), 
 'acc_entropy':pd.Series(acc_entropy),
 'max_depth':pd.Series(max_depth)})
# visualizing changes in parameters
plt.plot('max_depth','acc_gini', data=d, label='gini')
plt.plot('max_depth','acc_entropy', data=d, label='entropy')
plt.xlabel('max_depth')
plt.ylabel('accuracy')
plt.legend()

<matplotlib.legend.Legend at 0x7f565c8ab8b0>


rf_pruned =  RandomForestClassifier(criterion = "gini", n_estimators = 100,
                           n_jobs = -1,
                           oob_score = True,
                           bootstrap = True,
                           random_state = 42,
                           max_depth=3, min_samples_leaf=7)
rf_pruned.fit(X_train, y_train)
pred = rf_pruned.predict(X_test)
print('pruned', metrics.accuracy_score(y_test, pred))

pruned 0.78


importance = permutation_importance(rf_pruned, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 27.25528
Feature: 1, Score: 1.72745
Feature: 2, Score: 39.15547
Feature: 3, Score: 1.72745
Feature: 4, Score: 1.72745
Feature: 5, Score: 38.00384
Feature: 6, Score: 1.72745
Feature: 7, Score: 1.72745
Feature: 8, Score: 3.83877
Feature: 9, Score: 6.71785
Feature: 10, Score: 1.91939
Feature: 11, Score: 1.72745
Feature: 12, Score: 1.72745
Feature: 13, Score: 0.00000
Feature: 14, Score: 1.72745
Feature: 15, Score: 1.15163
Feature: 16, Score: 1.72745
Feature: 17, Score: 1.72745
Feature: 18, Score: 1.91939
Feature: 19, Score: 1.72745
Feature: 20, Score: 1.91939
Feature: 21, Score: 1.53551
Feature: 22, Score: 1.72745
Feature: 23, Score: 1.72745
Feature: 24, Score: 100.00000
Feature: 25, Score: 8.06142
Feature: 26, Score: 8.44530
Feature: 27, Score: 1.72745
Feature: 28, Score: 29.75048


y_score =rf_pruned.fit(X_train, y_train).predict(X_test)
fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw =4
plt.plot(fpr[4], tpr[4], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.96000, Cohen's Kappa Score: 0.70729
Confusion Matrix:
[[810  17   0   0   0]
 [  9  53   0   0   0]
 [  5   0   0   0   0]
 [  1   0   0   1   3]
 [  1   0   0   0   0]]
Classification Report:
              precision    recall  f1-score   support

           0       0.98      0.98      0.98       827
           1       0.76      0.85      0.80        62
           2       0.00      0.00      0.00         5
           3       1.00      0.20      0.33         5
           4       0.00      0.00      0.00         1

    accuracy                           0.96       900
   macro avg       0.55      0.41      0.42       900
weighted avg       0.96      0.96      0.96       900


estimator =rf_pruned.estimators_[5]
dot_data = StringIO()
export_graphviz(estimator, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True,feature_names = cols,class_names=['0','1','2','3','4'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
graph.write_png('images/case-1/RF-Pruned-DAST.png')
img0 = Image.open('images/case-1/RF-Pruned-DAST.png')

display.display(img0)


gbc= GradientBoostingClassifier( max_depth=7, min_samples_leaf=7,n_estimators = 100,random_state = 42)
                          
                          
                           
                           
gbc.fit(X_train, y_train.argmax(axis=1))
pred = gbc.predict(X_test)
print(pred.shape)
print('gbc', metrics.accuracy_score(y_test.argmax(axis=1), pred))

(900,)
gbc 0.9888888888888889


importance = permutation_importance(gbc, X_test, y_test.argmax(axis=1))
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 2.40385
Feature: 1, Score: 2.24359
Feature: 2, Score: 12.98077
Feature: 3, Score: 2.24359
Feature: 4, Score: 2.24359
Feature: 5, Score: 2.24359
Feature: 6, Score: 2.24359
Feature: 7, Score: 2.24359
Feature: 8, Score: 2.08333
Feature: 9, Score: 0.00000
Feature: 10, Score: 2.24359
Feature: 11, Score: 2.24359
Feature: 12, Score: 2.24359
Feature: 13, Score: 2.40385
Feature: 14, Score: 2.24359
Feature: 15, Score: 2.88462
Feature: 16, Score: 2.24359
Feature: 17, Score: 2.24359
Feature: 18, Score: 2.24359
Feature: 19, Score: 2.24359
Feature: 20, Score: 2.24359
Feature: 21, Score: 2.24359
Feature: 22, Score: 17.14744
Feature: 23, Score: 6.25000
Feature: 24, Score: 100.00000
Feature: 25, Score: 12.82051
Feature: 26, Score: 7.69231
Feature: 27, Score: 2.24359
Feature: 28, Score: 3.84615


y_score =pred

# # Binarize the output
y_train = label_binarize(y_train, classes=[0, 1, 2,3,4])
# n_classes = y_train.shape[1]
y_score = label_binarize(y_score, classes=[0, 1, 2,3,4])


fpr = dict()
tpr = dict()
roc_auc = dict()

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(5):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.98889, Cohen's Kappa Score: 0.89381
Confusion Matrix:
[[824   1   0   1   1]
 [  2  60   0   0   0]
 [  0   0   5   0   0]
 [  0   0   0   1   4]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      1.00      1.00       827
           1       0.98      0.97      0.98        62
           2       1.00      1.00      1.00         5
           3       0.33      0.20      0.25         5
           4       0.00      0.00      0.00         1

    accuracy                           0.99       900
   macro avg       0.66      0.63      0.64       900
weighted avg       0.99      0.99      0.99       900


# Extract single tree
estimator = gbc.estimators_[42, 0]
dot_data = StringIO()
export_graphviz(estimator, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True,feature_names = cols,class_names=['0','1','2','3','4'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
graph.write_png('images/case-1/GBC-DAST.png')
img0 = Image.open('images/case-1/GBC-DAST.png')

display.display(img0)


gbc_pruned = GradientBoostingClassifier(random_state = 42,n_estimators = 100,
                               max_depth=3, min_samples_leaf=7)
gbc_pruned.fit(X_train, y_train.argmax(axis=1))
pred = gbc_pruned.predict(X_test)
print(pred.shape)
print('gbc_pruned', metrics.accuracy_score(y_test.argmax(axis=1), pred))

(900,)
gbc_pruned 0.9855555555555555


importance = permutation_importance(gbc_pruned, X_test, y_test.argmax(axis=1))
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 0.69324
Feature: 1, Score: 3.46620
Feature: 2, Score: 12.47834
Feature: 3, Score: 2.59965
Feature: 4, Score: 2.59965
Feature: 5, Score: 3.29289
Feature: 6, Score: 2.59965
Feature: 7, Score: 2.59965
Feature: 8, Score: 0.86655
Feature: 9, Score: 0.00000
Feature: 10, Score: 2.42634
Feature: 11, Score: 2.59965
Feature: 12, Score: 1.55979
Feature: 13, Score: 2.77296
Feature: 14, Score: 2.59965
Feature: 15, Score: 3.29289
Feature: 16, Score: 2.59965
Feature: 17, Score: 2.59965
Feature: 18, Score: 2.59965
Feature: 19, Score: 2.59965
Feature: 20, Score: 2.59965
Feature: 21, Score: 1.73310
Feature: 22, Score: 18.54419
Feature: 23, Score: 7.10572
Feature: 24, Score: 100.00000
Feature: 25, Score: 14.21144
Feature: 26, Score: 10.39861
Feature: 27, Score: 2.59965
Feature: 28, Score: 2.25303


y_score =pred

# # Binarize the output
y_train = label_binarize(y_train, classes=[0, 1, 2,3,4])
# n_classes = y_train.shape[1]
y_score = label_binarize(y_score, classes=[0, 1, 2,3,4])


fpr = dict()
tpr = dict()
roc_auc = dict()

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(5):

    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.98556, Cohen's Kappa Score: 0.86982
Confusion Matrix:
[[823   2   0   1   1]
 [  4  58   0   0   0]
 [  1   0   4   0   0]
 [  0   0   0   2   3]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       0.99      1.00      0.99       827
           1       0.97      0.94      0.95        62
           2       1.00      0.80      0.89         5
           3       0.50      0.40      0.44         5
           4       0.00      0.00      0.00         1

    accuracy                           0.99       900
   macro avg       0.69      0.63      0.66       900
weighted avg       0.99      0.99      0.99       900


estimator =gbc_pruned.estimators_[42, 0]
dot_data = StringIO()
export_graphviz(estimator, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True,feature_names =cols,class_names=['0','1','2','3','4'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
graph.write_png('images/case-1/GBC-Pruned-DAST.png')
img0 = Image.open('images/case-1/GBC-Pruned-DAST.png')

display.display(img0)


gnb = GaussianNB()
gnb.partial_fit( X_train,y_train.argmax(axis=1), np.unique(y_train.argmax(axis=1) ))
pred = gnb.predict(X_test)
print(pred.shape)
print('gnb', metrics.accuracy_score(y_test.argmax(axis=1), pred))

(900,)
gnb 0.9588888888888889


importance = permutation_importance(gnb, X_test, y_test.argmax(axis=1))
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

Feature: 0, Score: 16.38889
Feature: 1, Score: 10.83333
Feature: 2, Score: 66.66667
Feature: 3, Score: 36.94444
Feature: 4, Score: 3.88889
Feature: 5, Score: 61.11111
Feature: 6, Score: 3.33333
Feature: 7, Score: 6.94444
Feature: 8, Score: 3.61111
Feature: 9, Score: 13.88889
Feature: 10, Score: 3.33333
Feature: 11, Score: 3.33333
Feature: 12, Score: 1.94444
Feature: 13, Score: 0.00000
Feature: 14, Score: 4.16667
Feature: 15, Score: 2.77778
Feature: 16, Score: 0.83333
Feature: 17, Score: 3.61111
Feature: 18, Score: 2.77778
Feature: 19, Score: 3.05556
Feature: 20, Score: 5.00000
Feature: 21, Score: 5.83333
Feature: 22, Score: 3.61111
Feature: 23, Score: 13.88889
Feature: 24, Score: 100.00000
Feature: 25, Score: 16.94444
Feature: 26, Score: 16.66667
Feature: 27, Score: 3.33333
Feature: 28, Score: 3.61111


y_score =pred

# # Binarize the output
y_train = label_binarize(y_train, classes=[0, 1, 2,3,4])
# n_classes = y_train.shape[1]
y_score = label_binarize(y_score, classes=[0, 1, 2,3,4])


fpr = dict()
tpr = dict()
roc_auc = dict()

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(5):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.95889, Cohen's Kappa Score: 0.79660
Confusion Matrix:
[[801  19   5   2   0]
 [  3  57   2   0   0]
 [  0   0   4   1   0]
 [  0   0   1   1   3]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      0.97      0.98       827
           1       0.75      0.92      0.83        62
           2       0.33      0.80      0.47         5
           3       0.20      0.20      0.20         5
           4       0.00      0.00      0.00         1

    accuracy                           0.96       900
   macro avg       0.46      0.58      0.50       900
weighted avg       0.97      0.96      0.96       900


svm1 =OneVsRestClassifier(svm.SVC(kernel='linear', probability=True,
                                 random_state=1))
                                  
svm1.fit(X_train, y_train)                                 
pred = svm1.predict(X_test)
print('svm', metrics.accuracy_score(y_test, pred))

svm 0.97


# get importance
importance =svm1.coef_.argmax(axis=0)
print(importance.shape)
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
print(importance.shape)
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

(29,)
(29,)
Feature: 0, Score: 0.00000
Feature: 1, Score: 50.00000
Feature: 2, Score: 50.00000
Feature: 3, Score: 25.00000
Feature: 4, Score: 50.00000
Feature: 5, Score: 50.00000
Feature: 6, Score: 100.00000
Feature: 7, Score: 0.00000
Feature: 8, Score: 50.00000
Feature: 9, Score: 100.00000
Feature: 10, Score: 75.00000
Feature: 11, Score: 0.00000
Feature: 12, Score: 25.00000
Feature: 13, Score: 75.00000
Feature: 14, Score: 0.00000
Feature: 15, Score: 0.00000
Feature: 16, Score: 0.00000
Feature: 17, Score: 25.00000
Feature: 18, Score: 0.00000
Feature: 19, Score: 0.00000
Feature: 20, Score: 75.00000
Feature: 21, Score: 0.00000
Feature: 22, Score: 0.00000
Feature: 23, Score: 25.00000
Feature: 24, Score: 25.00000
Feature: 25, Score: 50.00000
Feature: 26, Score: 75.00000
Feature: 27, Score: 100.00000
Feature: 28, Score: 50.00000


importance = permutation_importance(svm1, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
print(importance.shape)
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

(29,)
Feature: 0, Score: 7.33453
Feature: 1, Score: 2.68336
Feature: 2, Score: 15.92129
Feature: 3, Score: 2.86225
Feature: 4, Score: 2.68336
Feature: 5, Score: 10.01789
Feature: 6, Score: 2.68336
Feature: 7, Score: 2.68336
Feature: 8, Score: 2.68336
Feature: 9, Score: 0.00000
Feature: 10, Score: 3.39893
Feature: 11, Score: 2.68336
Feature: 12, Score: 3.57782
Feature: 13, Score: 2.14669
Feature: 14, Score: 2.68336
Feature: 15, Score: 7.87120
Feature: 16, Score: 2.68336
Feature: 17, Score: 2.68336
Feature: 18, Score: 2.50447
Feature: 19, Score: 2.68336
Feature: 20, Score: 4.29338
Feature: 21, Score: 3.57782
Feature: 22, Score: 6.61896
Feature: 23, Score: 5.72451
Feature: 24, Score: 100.00000
Feature: 25, Score: 15.02683
Feature: 26, Score: 9.83900
Feature: 27, Score: 2.68336
Feature: 28, Score: 3.39893


y_score = svm1.fit(X_train, y_train).decision_function(X_test)

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw =4
plt.plot(fpr[4], tpr[4], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.97556, Cohen's Kappa Score: 0.88444
Confusion Matrix:
[[811  15   0   1   0]
 [  1  61   0   0   0]
 [  1   0   4   0   0]
 [  0   0   1   2   2]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      0.98      0.99       827
           1       0.80      0.98      0.88        62
           2       0.80      0.80      0.80         5
           3       0.50      0.40      0.44         5
           4       0.00      0.00      0.00         1

    accuracy                           0.98       900
   macro avg       0.62      0.63      0.62       900
weighted avg       0.98      0.98      0.98       900


rbf_svm1 =OneVsRestClassifier(svm.SVC(kernel='rbf', probability=True,
                                 random_state=1))
                                  
rbf_svm1.fit(X_train, y_train)                                 
pred = rbf_svm1.predict(X_test)
print('rbf_svm', metrics.accuracy_score(y_test, pred))

rbf_svm 0.9711111111111111


importance = permutation_importance(rbf_svm1, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
print(importance.shape)
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

(29,)
Feature: 0, Score: 0.00000
Feature: 1, Score: 4.74576
Feature: 2, Score: 6.44068
Feature: 3, Score: 4.74576
Feature: 4, Score: 3.89831
Feature: 5, Score: 5.08475
Feature: 6, Score: 3.89831
Feature: 7, Score: 3.89831
Feature: 8, Score: 3.72881
Feature: 9, Score: 1.35593
Feature: 10, Score: 4.40678
Feature: 11, Score: 3.89831
Feature: 12, Score: 3.89831
Feature: 13, Score: 3.05085
Feature: 14, Score: 3.89831
Feature: 15, Score: 6.77966
Feature: 16, Score: 3.89831
Feature: 17, Score: 3.89831
Feature: 18, Score: 3.72881
Feature: 19, Score: 3.89831
Feature: 20, Score: 4.23729
Feature: 21, Score: 4.74576
Feature: 22, Score: 8.64407
Feature: 23, Score: 6.44068
Feature: 24, Score: 100.00000
Feature: 25, Score: 13.72881
Feature: 26, Score: 9.32203
Feature: 27, Score: 3.89831
Feature: 28, Score: 4.40678


y_score =rbf_svm1.fit(X_train, y_train).decision_function(X_test)

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw =4
plt.plot(fpr[4], tpr[4], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.97222, Cohen's Kappa Score: 0.87619
Confusion Matrix:
[[811  15   0   1   0]
 [  3  59   0   0   0]
 [  1   0   4   0   0]
 [  0   0   1   1   3]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      0.98      0.99       827
           1       0.80      0.95      0.87        62
           2       0.80      0.80      0.80         5
           3       0.33      0.20      0.25         5
           4       0.00      0.00      0.00         1

    accuracy                           0.97       900
   macro avg       0.59      0.59      0.58       900
weighted avg       0.98      0.97      0.97       900


poly_svm1 =OneVsRestClassifier(svm.SVC(kernel='poly',probability=True,
                                 random_state=1))
                                  
poly_svm1.fit(X_train, y_train)                                 
pred = poly_svm1.predict(X_test)
print('svm_poly', metrics.accuracy_score(y_test, pred))

svm_poly 0.9755555555555555


# importance = permutation_importance(poly_svm1, X_test, y_test)
# importance =importance.importances_mean
# importance = (importance-min(importance))/(max(importance)-min(importance))*100
# plt.figure(figsize=(20,10))
# print(importance.shape)
# for i,v in enumerate(importance):
#     print('Feature: %0d, Score: %.5f' % (i,v))
# # plot feature importance
# sns.barplot([x for x in range(len(importance))], importance)
# pyplot.show()


y_score= poly_svm1.fit(X_train, y_train).decision_function(X_test)

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw =4
plt.plot(fpr[4], tpr[4], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.97778, Cohen's Kappa Score: 0.87380
Confusion Matrix:
[[818   8   0   1   0]
 [  2  59   1   0   0]
 [  3   0   2   0   0]
 [  0   0   0   1   4]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       0.99      0.99      0.99       827
           1       0.88      0.95      0.91        62
           2       0.67      0.40      0.50         5
           3       0.33      0.20      0.25         5
           4       0.00      0.00      0.00         1

    accuracy                           0.98       900
   macro avg       0.57      0.51      0.53       900
weighted avg       0.98      0.98      0.98       900


lin_svc_svm1 =OneVsRestClassifier(svm.LinearSVC(random_state=1))
                                  
lin_svc_svm1.fit(X_train, y_train)                                 
pred = lin_svc_svm1.predict(X_test)
print('lin_svc_poly', metrics.accuracy_score(y_test, pred))

lin_svc_poly 0.97


importance = permutation_importance(lin_svc_svm1, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
print(importance.shape)
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

(29,)
Feature: 0, Score: 2.15054
Feature: 1, Score: 2.15054
Feature: 2, Score: 24.91039
Feature: 3, Score: 5.19713
Feature: 4, Score: 1.43369
Feature: 5, Score: 13.26165
Feature: 6, Score: 1.43369
Feature: 7, Score: 1.43369
Feature: 8, Score: 0.00000
Feature: 9, Score: 0.00000
Feature: 10, Score: 0.35842
Feature: 11, Score: 1.43369
Feature: 12, Score: 1.43369
Feature: 13, Score: 0.89606
Feature: 14, Score: 1.43369
Feature: 15, Score: 4.48029
Feature: 16, Score: 1.43369
Feature: 17, Score: 1.43369
Feature: 18, Score: 1.61290
Feature: 19, Score: 1.43369
Feature: 20, Score: 2.86738
Feature: 21, Score: 1.43369
Feature: 22, Score: 5.73477
Feature: 23, Score: 4.30108
Feature: 24, Score: 100.00000
Feature: 25, Score: 13.62007
Feature: 26, Score: 7.88530
Feature: 27, Score: 1.43369
Feature: 28, Score: 1.61290


y_score= lin_svc_svm1.fit(X_train, y_train).decision_function(X_test)

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw =4
plt.plot(fpr[4], tpr[4], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.97444, Cohen's Kappa Score: 0.84491
Confusion Matrix:
[[810  15   0   1   1]
 [  1  61   0   0   0]
 [  0   0   4   0   1]
 [  0   0   1   2   2]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      0.98      0.99       827
           1       0.80      0.98      0.88        62
           2       0.80      0.80      0.80         5
           3       0.50      0.40      0.44         5
           4       0.00      0.00      0.00         1

    accuracy                           0.97       900
   macro avg       0.62      0.63      0.62       900
weighted avg       0.98      0.97      0.98       900


mlp = MLPClassifier(hidden_layer_sizes=(50,50,50))
                                  
mlp.fit(X_train, y_train)                                 
pred = mlp.predict(X_test)
print('mlp', metrics.accuracy_score(y_test, pred))

mlp 0.9844444444444445


importance = permutation_importance(mlp, X_test, y_test)
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
print(importance.shape)
plt.figure(figsize=(20,10))

for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)

pyplot.show()

(29,)
Feature: 0, Score: 2.18688
Feature: 1, Score: 4.77137
Feature: 2, Score: 24.45328
Feature: 3, Score: 10.13917
Feature: 4, Score: 3.57853
Feature: 5, Score: 18.29026
Feature: 6, Score: 2.98211
Feature: 7, Score: 2.98211
Feature: 8, Score: 1.78926
Feature: 9, Score: 0.79523
Feature: 10, Score: 1.59046
Feature: 11, Score: 2.98211
Feature: 12, Score: 3.18091
Feature: 13, Score: 2.18688
Feature: 14, Score: 2.98211
Feature: 15, Score: 3.77734
Feature: 16, Score: 2.98211
Feature: 17, Score: 2.98211
Feature: 18, Score: 3.18091
Feature: 19, Score: 2.98211
Feature: 20, Score: 2.98211
Feature: 21, Score: 3.77734
Feature: 22, Score: 14.51292
Feature: 23, Score: 5.96421
Feature: 24, Score: 100.00000
Feature: 25, Score: 13.51889
Feature: 26, Score: 12.92247
Feature: 27, Score: 2.98211
Feature: 28, Score: 0.00000


y_score= mlp.fit(X_train, y_train).predict(X_test)

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw =4
plt.plot(fpr[4], tpr[4], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.98556, Cohen's Kappa Score: 0.93985
Confusion Matrix:
[[823   4   0   0   0]
 [  4  58   0   0   0]
 [  1   0   4   0   0]
 [  0   0   1   2   2]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       0.99      1.00      0.99       827
           1       0.94      0.94      0.94        62
           2       0.80      0.80      0.80         5
           3       0.67      0.40      0.50         5
           4       0.00      0.00      0.00         1

    accuracy                           0.99       900
   macro avg       0.68      0.63      0.65       900
weighted avg       0.99      0.99      0.99       900


def get_model():
    input_layer=tf.keras.layers.Input((29,))
    net=tf.keras.layers.Dense(64,'relu')(input_layer)
    net=tf.keras.layers.Dense(128,'relu')(net)
    net=tf.keras.layers.Dense(128,'relu')(net)
    net=tf.keras.layers.Dense(128,'relu')(net)
    net=tf.keras.layers.Dense(256,'relu')(net)
    net=tf.keras.layers.Dense(256,'relu')(net)    
    output=tf.keras.layers.Dense(1,'sigmoid')(net)
    model=tf.keras.Model(inputs=[input_layer],outputs=[output])
    return model
def train_model(X_train,y_train,X_test,y_test):
    
        model=get_model()
        model.compile(loss='categorical_crossentropy',optimizer='adam',metrics=['accuracy'])
        
        history=model.fit(X_train,
                      y_train,
                      batch_size=32,
                      epochs=500,
                      validation_data=(X_test,y_test))

    
        return model,history
 
class Neural_Network:
    def __init__(self,X_train,y_train,X_test,y_test):
        
        self.model,self.history=train_model(X_train,y_train,X_test,y_test)
                                                             
        
    
        
    def predict_classes(self,X):
        l=self.model.predict(X)
        i=0
        final=[]
        while i<len(l):
            temp=l[i][0]
            temp_2=float(float(1)-l[i][0])
           # print(temp)
           # print(temp_2)
            arr=np.array([temp,temp_2],dtype='float32')
            i+=1
            final.append(arr)
        return np.array(final, dtype='float32')
        
    def summary(self):
        self.model.summary()


print(y_train.shape)
from sklearn.metrics import accuracy_score,f1_score
model_nn=Neural_Network(X_train,y_train.argmax(axis=1), X_test,y_test.argmax(axis=1))
print(model_nn.predict_classes(X_train).astype(float))

(30000, 5)
Epoch 1/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 2/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 3/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 4/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 5/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 6/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 7/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 8/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 9/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 10/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 11/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 12/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 13/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 14/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 15/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 16/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 17/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 18/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 19/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 20/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 21/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 22/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 23/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 24/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 25/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 26/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 27/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 28/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 29/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 30/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 31/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 32/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 33/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 34/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 35/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 36/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 37/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 38/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 39/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 40/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 41/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 42/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 43/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 44/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 45/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 46/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 47/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 48/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 49/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 50/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 51/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 52/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 53/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 54/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 55/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 56/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 57/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 58/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 59/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 60/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 61/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 62/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 63/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 64/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 65/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 66/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 67/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 68/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 69/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 70/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 71/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 72/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 73/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 74/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 75/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 76/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 77/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 78/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 79/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 80/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 81/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 82/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 83/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 84/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 85/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 86/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 87/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 88/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 89/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 90/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 91/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 92/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 93/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 94/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 95/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 96/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 97/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 98/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 99/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 100/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 101/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 102/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 103/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 104/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 105/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 106/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 107/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 108/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 109/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 110/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 111/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 112/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 113/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 114/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 115/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 116/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 117/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 118/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 119/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 120/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 121/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 122/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 123/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 124/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 125/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 126/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 127/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 128/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 129/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 130/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 131/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 132/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 133/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 134/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 135/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 136/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 137/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 138/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 139/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 140/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 141/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 142/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 143/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 144/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 145/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 146/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 147/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 148/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 149/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 150/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 151/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 152/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 153/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 154/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 155/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 156/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 157/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 158/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 159/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 160/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 161/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 162/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 163/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 164/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 165/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 166/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 167/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 168/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 169/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 170/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 171/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 172/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 173/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 174/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 175/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 176/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 177/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 178/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 179/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 180/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 181/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 182/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 183/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 184/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 185/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 186/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 187/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 188/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 189/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 190/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 191/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 192/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 193/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 194/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 195/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 196/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 197/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 198/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 199/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 200/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 201/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 202/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 203/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 204/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 205/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 206/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 207/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 208/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 209/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 210/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 211/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 212/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 213/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 214/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 215/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 216/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 217/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 218/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 219/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 220/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 221/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 222/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 223/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 224/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 225/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 226/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 227/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 228/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 229/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 230/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 231/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 232/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 233/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 234/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 235/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 236/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 237/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 238/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 239/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 240/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 241/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 242/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 243/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 244/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 245/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 246/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 247/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 248/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 249/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 250/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 251/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 252/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 253/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 254/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 255/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 256/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 257/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 258/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 259/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 260/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 261/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 262/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 263/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 264/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 265/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 266/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 267/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 268/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 269/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 270/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 271/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 272/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 273/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 274/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 275/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 276/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 277/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 278/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 279/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 280/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 281/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 282/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 283/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 284/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 285/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 286/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 287/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 288/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 289/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 290/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 291/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 292/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 293/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 294/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 295/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 296/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 297/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 298/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 299/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 300/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 301/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 302/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 303/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 304/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 305/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 306/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 307/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 308/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 309/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 310/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 311/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 312/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 313/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 314/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 315/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 316/500
938/938 [==============================] - 1s 2ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 317/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 318/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 319/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 320/500
938/938 [==============================] - 1s 2ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 321/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 322/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 323/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 324/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 325/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 326/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 327/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 328/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 329/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 330/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 331/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 332/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 333/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 334/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 335/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 336/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 337/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 338/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 339/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 340/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 341/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 342/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 343/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 344/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 345/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 346/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 347/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 348/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 349/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 350/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 351/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 352/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 353/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 354/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 355/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 356/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 357/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 358/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 359/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 360/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 361/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 362/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 363/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 364/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 365/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 366/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 367/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 368/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 369/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 370/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 371/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 372/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 373/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 374/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 375/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 376/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 377/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 378/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 379/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 380/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 381/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 382/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 383/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 384/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 385/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 386/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 387/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 388/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 389/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 390/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 391/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 392/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 393/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 394/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 395/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 396/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 397/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 398/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 399/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 400/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 401/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 402/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 403/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 404/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 405/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 406/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 407/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 408/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 409/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 410/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 411/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 412/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 413/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 414/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 415/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 416/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 417/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 418/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 419/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 420/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 421/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 422/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 423/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 424/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 425/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 426/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 427/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 428/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 429/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 430/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 431/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 432/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 433/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 434/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 435/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 436/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 437/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 438/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 439/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 440/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 441/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 442/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 443/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 444/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 445/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 446/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 447/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 448/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 449/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 450/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 451/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 452/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 453/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 454/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 455/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 456/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 457/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 458/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 459/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 460/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 461/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 462/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 463/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 464/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 465/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 466/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 467/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 468/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 469/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 470/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 471/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 472/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 473/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 474/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 475/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 476/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 477/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 478/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 479/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 480/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 481/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 482/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 483/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 484/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 485/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 486/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 487/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 488/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 489/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 490/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 491/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 492/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 493/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 494/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 495/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 496/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 497/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 498/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 499/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
Epoch 500/500
938/938 [==============================] - 1s 1ms/step - loss: 2.3842e-07 - accuracy: 0.2768 - val_loss: 1.2053e-08 - val_accuracy: 0.5078
[[0.50295353 0.49704647]
 [0.50048244 0.49951756]
 [0.50007421 0.49992579]
 ...
 [0.49994713 0.50005287]
 [0.49994713 0.50005287]
 [0.50315309 0.49684691]]


params = {'boosting_type': 'gbdt',
              'objective': 'multiclass',
              'metric':'multi_logloss',
              'num_leaves': 40,
              'learning_rate':0.01,
              'num_class':5,
              'feature_fraction': 0.9
              }


lgb_train = lgb.Dataset(X_train, y_train.argmax(axis=1))
lgb_eval = lgb.Dataset(X_test, y_test.argmax(axis=1), reference=lgb_train)
gbm = lgb.train(params,
    lgb_train,
    num_boost_round=2000,
    valid_sets=[lgb_train, lgb_eval],
    valid_names=['train','valid'],
   )

[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002398 seconds.
You can set `force_col_wise=true` to remove the overhead.
[LightGBM] [Info] Total Bins 5794
[LightGBM] [Info] Number of data points in the train set: 30000, number of used features: 28
[LightGBM] [Info] Start training from score -1.609438
[LightGBM] [Info] Start training from score -1.609438
[LightGBM] [Info] Start training from score -1.609438
[LightGBM] [Info] Start training from score -1.609438
[LightGBM] [Info] Start training from score -1.609438
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1]	train's multi_logloss: 1.56982	valid's multi_logloss: 1.57101
[2]	train's multi_logloss: 1.53203	valid's multi_logloss: 1.53461
[3]	train's multi_logloss: 1.4955	valid's multi_logloss: 1.49881
[4]	train's multi_logloss: 1.46064	valid's multi_logloss: 1.46771
[5]	train's multi_logloss: 1.42701	valid's multi_logloss: 1.43479
[6]	train's multi_logloss: 1.39444	valid's multi_logloss: 1.40285
[7]	train's multi_logloss: 1.36303	valid's multi_logloss: 1.37208
[8]	train's multi_logloss: 1.33291	valid's multi_logloss: 1.34498
[9]	train's multi_logloss: 1.30398	valid's multi_logloss: 1.31734
[10]	train's multi_logloss: 1.27571	valid's multi_logloss: 1.28994
[11]	train's multi_logloss: 1.24828	valid's multi_logloss: 1.26292
[12]	train's multi_logloss: 1.22182	valid's multi_logloss: 1.23705
[13]	train's multi_logloss: 1.19619	valid's multi_logloss: 1.2121
[14]	train's multi_logloss: 1.1712	valid's multi_logloss: 1.18767
[15]	train's multi_logloss: 1.14693	valid's multi_logloss: 1.16383
[16]	train's multi_logloss: 1.12351	valid's multi_logloss: 1.141
[17]	train's multi_logloss: 1.10062	valid's multi_logloss: 1.11855
[18]	train's multi_logloss: 1.07839	valid's multi_logloss: 1.09664
[19]	train's multi_logloss: 1.05713	valid's multi_logloss: 1.07633
[20]	train's multi_logloss: 1.03606	valid's multi_logloss: 1.05573
[21]	train's multi_logloss: 1.01555	valid's multi_logloss: 1.03565
[22]	train's multi_logloss: 0.995594	valid's multi_logloss: 1.01618
[23]	train's multi_logloss: 0.976134	valid's multi_logloss: 0.997085
[24]	train's multi_logloss: 0.957434	valid's multi_logloss: 0.979922
[25]	train's multi_logloss: 0.938944	valid's multi_logloss: 0.961745
[26]	train's multi_logloss: 0.921144	valid's multi_logloss: 0.944807
[27]	train's multi_logloss: 0.903568	valid's multi_logloss: 0.927624
[28]	train's multi_logloss: 0.886521	valid's multi_logloss: 0.911465
[29]	train's multi_logloss: 0.869758	valid's multi_logloss: 0.894951
[30]	train's multi_logloss: 0.853654	valid's multi_logloss: 0.879311
[31]	train's multi_logloss: 0.837741	valid's multi_logloss: 0.863738
[32]	train's multi_logloss: 0.822125	valid's multi_logloss: 0.848358
[33]	train's multi_logloss: 0.806874	valid's multi_logloss: 0.833317
[34]	train's multi_logloss: 0.791967	valid's multi_logloss: 0.818739
[35]	train's multi_logloss: 0.777405	valid's multi_logloss: 0.804548
[36]	train's multi_logloss: 0.76315	valid's multi_logloss: 0.790528
[37]	train's multi_logloss: 0.749217	valid's multi_logloss: 0.776809
[38]	train's multi_logloss: 0.735816	valid's multi_logloss: 0.763696
[39]	train's multi_logloss: 0.722473	valid's multi_logloss: 0.750607
[40]	train's multi_logloss: 0.709417	valid's multi_logloss: 0.737788
[41]	train's multi_logloss: 0.696641	valid's multi_logloss: 0.725216
[42]	train's multi_logloss: 0.684149	valid's multi_logloss: 0.713063
[43]	train's multi_logloss: 0.671988	valid's multi_logloss: 0.702283
[44]	train's multi_logloss: 0.659998	valid's multi_logloss: 0.69045
[45]	train's multi_logloss: 0.648338	valid's multi_logloss: 0.679397
[46]	train's multi_logloss: 0.63688	valid's multi_logloss: 0.668225
[47]	train's multi_logloss: 0.625614	valid's multi_logloss: 0.65717
[48]	train's multi_logloss: 0.614727	valid's multi_logloss: 0.646779
[49]	train's multi_logloss: 0.603915	valid's multi_logloss: 0.636103
[50]	train's multi_logloss: 0.593441	valid's multi_logloss: 0.625978
[51]	train's multi_logloss: 0.583058	valid's multi_logloss: 0.61587
[52]	train's multi_logloss: 0.572918	valid's multi_logloss: 0.605933
[53]	train's multi_logloss: 0.563057	valid's multi_logloss: 0.596658
[54]	train's multi_logloss: 0.553434	valid's multi_logloss: 0.58757
[55]	train's multi_logloss: 0.543899	valid's multi_logloss: 0.578557
[56]	train's multi_logloss: 0.534477	valid's multi_logloss: 0.569282
[57]	train's multi_logloss: 0.525311	valid's multi_logloss: 0.560642
[58]	train's multi_logloss: 0.51626	valid's multi_logloss: 0.551776
[59]	train's multi_logloss: 0.507376	valid's multi_logloss: 0.543017
[60]	train's multi_logloss: 0.498766	valid's multi_logloss: 0.534883
[61]	train's multi_logloss: 0.490253	valid's multi_logloss: 0.526488
[62]	train's multi_logloss: 0.48187	valid's multi_logloss: 0.518304
[63]	train's multi_logloss: 0.47371	valid's multi_logloss: 0.510602
[64]	train's multi_logloss: 0.465709	valid's multi_logloss: 0.503015
[65]	train's multi_logloss: 0.457786	valid's multi_logloss: 0.495212
[66]	train's multi_logloss: 0.450009	valid's multi_logloss: 0.487537
[67]	train's multi_logloss: 0.442384	valid's multi_logloss: 0.480029
[68]	train's multi_logloss: 0.43489	valid's multi_logloss: 0.472631
[69]	train's multi_logloss: 0.427539	valid's multi_logloss: 0.465414
[70]	train's multi_logloss: 0.420361	valid's multi_logloss: 0.458374
[71]	train's multi_logloss: 0.413317	valid's multi_logloss: 0.451439
[72]	train's multi_logloss: 0.406383	valid's multi_logloss: 0.44457
[73]	train's multi_logloss: 0.399671	valid's multi_logloss: 0.438128
[74]	train's multi_logloss: 0.392959	valid's multi_logloss: 0.431494
[75]	train's multi_logloss: 0.386399	valid's multi_logloss: 0.425035
[76]	train's multi_logloss: 0.379922	valid's multi_logloss: 0.418528
[77]	train's multi_logloss: 0.373563	valid's multi_logloss: 0.412177
[78]	train's multi_logloss: 0.36732	valid's multi_logloss: 0.406025
[79]	train's multi_logloss: 0.361189	valid's multi_logloss: 0.399989
[80]	train's multi_logloss: 0.355168	valid's multi_logloss: 0.39406
[81]	train's multi_logloss: 0.349359	valid's multi_logloss: 0.388502
[82]	train's multi_logloss: 0.343552	valid's multi_logloss: 0.382755
[83]	train's multi_logloss: 0.337852	valid's multi_logloss: 0.377177
[84]	train's multi_logloss: 0.332342	valid's multi_logloss: 0.371836
[85]	train's multi_logloss: 0.326834	valid's multi_logloss: 0.366478
[86]	train's multi_logloss: 0.32142	valid's multi_logloss: 0.361184
[87]	train's multi_logloss: 0.316094	valid's multi_logloss: 0.355882
[88]	train's multi_logloss: 0.310872	valid's multi_logloss: 0.350671
[89]	train's multi_logloss: 0.305735	valid's multi_logloss: 0.345625
[90]	train's multi_logloss: 0.300689	valid's multi_logloss: 0.340641
[91]	train's multi_logloss: 0.295809	valid's multi_logloss: 0.336222
[92]	train's multi_logloss: 0.290972	valid's multi_logloss: 0.331637
[93]	train's multi_logloss: 0.286184	valid's multi_logloss: 0.326922
[94]	train's multi_logloss: 0.281479	valid's multi_logloss: 0.322276
[95]	train's multi_logloss: 0.276875	valid's multi_logloss: 0.317696
[96]	train's multi_logloss: 0.272376	valid's multi_logloss: 0.31343
[97]	train's multi_logloss: 0.267908	valid's multi_logloss: 0.309028
[98]	train's multi_logloss: 0.263519	valid's multi_logloss: 0.304733
[99]	train's multi_logloss: 0.259222	valid's multi_logloss: 0.300581
[100]	train's multi_logloss: 0.255034	valid's multi_logloss: 0.296672
[101]	train's multi_logloss: 0.250864	valid's multi_logloss: 0.292528
[102]	train's multi_logloss: 0.246764	valid's multi_logloss: 0.288501
[103]	train's multi_logloss: 0.242781	valid's multi_logloss: 0.284682
[104]	train's multi_logloss: 0.23882	valid's multi_logloss: 0.280846
[105]	train's multi_logloss: 0.234924	valid's multi_logloss: 0.277008
[106]	train's multi_logloss: 0.231106	valid's multi_logloss: 0.273358
[107]	train's multi_logloss: 0.227352	valid's multi_logloss: 0.269684
[108]	train's multi_logloss: 0.223649	valid's multi_logloss: 0.266028
[109]	train's multi_logloss: 0.220007	valid's multi_logloss: 0.262446
[110]	train's multi_logloss: 0.216428	valid's multi_logloss: 0.258919
[111]	train's multi_logloss: 0.212909	valid's multi_logloss: 0.25536
[112]	train's multi_logloss: 0.209451	valid's multi_logloss: 0.251997
[113]	train's multi_logloss: 0.206079	valid's multi_logloss: 0.248708
[114]	train's multi_logloss: 0.202767	valid's multi_logloss: 0.245564
[115]	train's multi_logloss: 0.199494	valid's multi_logloss: 0.242353
[116]	train's multi_logloss: 0.196263	valid's multi_logloss: 0.239184
[117]	train's multi_logloss: 0.193083	valid's multi_logloss: 0.236084
[118]	train's multi_logloss: 0.18996	valid's multi_logloss: 0.232996
[119]	train's multi_logloss: 0.186924	valid's multi_logloss: 0.230122
[120]	train's multi_logloss: 0.183929	valid's multi_logloss: 0.227276
[121]	train's multi_logloss: 0.180984	valid's multi_logloss: 0.224445
[122]	train's multi_logloss: 0.178065	valid's multi_logloss: 0.221628
[123]	train's multi_logloss: 0.175189	valid's multi_logloss: 0.218781
[124]	train's multi_logloss: 0.172366	valid's multi_logloss: 0.216082
[125]	train's multi_logloss: 0.169609	valid's multi_logloss: 0.213368
[126]	train's multi_logloss: 0.16688	valid's multi_logloss: 0.210751
[127]	train's multi_logloss: 0.164196	valid's multi_logloss: 0.208097
[128]	train's multi_logloss: 0.161554	valid's multi_logloss: 0.205465
[129]	train's multi_logloss: 0.158956	valid's multi_logloss: 0.202952
[130]	train's multi_logloss: 0.156406	valid's multi_logloss: 0.200527
[131]	train's multi_logloss: 0.153931	valid's multi_logloss: 0.198116
[132]	train's multi_logloss: 0.151458	valid's multi_logloss: 0.195601
[133]	train's multi_logloss: 0.149027	valid's multi_logloss: 0.19326
[134]	train's multi_logloss: 0.146636	valid's multi_logloss: 0.190944
[135]	train's multi_logloss: 0.144285	valid's multi_logloss: 0.188686
[136]	train's multi_logloss: 0.142	valid's multi_logloss: 0.18649
[137]	train's multi_logloss: 0.139725	valid's multi_logloss: 0.184294
[138]	train's multi_logloss: 0.137506	valid's multi_logloss: 0.182127
[139]	train's multi_logloss: 0.135306	valid's multi_logloss: 0.180037
[140]	train's multi_logloss: 0.133141	valid's multi_logloss: 0.177964
[141]	train's multi_logloss: 0.131051	valid's multi_logloss: 0.176053
[142]	train's multi_logloss: 0.128956	valid's multi_logloss: 0.174057
[143]	train's multi_logloss: 0.126897	valid's multi_logloss: 0.172084
[144]	train's multi_logloss: 0.124868	valid's multi_logloss: 0.170079
[145]	train's multi_logloss: 0.122872	valid's multi_logloss: 0.168044
[146]	train's multi_logloss: 0.12093	valid's multi_logloss: 0.166257
[147]	train's multi_logloss: 0.119	valid's multi_logloss: 0.164284
[148]	train's multi_logloss: 0.117103	valid's multi_logloss: 0.162519
[149]	train's multi_logloss: 0.11524	valid's multi_logloss: 0.160745
[150]	train's multi_logloss: 0.113405	valid's multi_logloss: 0.158977
[151]	train's multi_logloss: 0.111598	valid's multi_logloss: 0.157274
[152]	train's multi_logloss: 0.109823	valid's multi_logloss: 0.155621
[153]	train's multi_logloss: 0.108082	valid's multi_logloss: 0.15398
[154]	train's multi_logloss: 0.106381	valid's multi_logloss: 0.152434
[155]	train's multi_logloss: 0.104689	valid's multi_logloss: 0.150824
[156]	train's multi_logloss: 0.103026	valid's multi_logloss: 0.149248
[157]	train's multi_logloss: 0.101405	valid's multi_logloss: 0.14777
[158]	train's multi_logloss: 0.0997956	valid's multi_logloss: 0.146282
[159]	train's multi_logloss: 0.0982113	valid's multi_logloss: 0.144794
[160]	train's multi_logloss: 0.0966668	valid's multi_logloss: 0.143397
[161]	train's multi_logloss: 0.0951482	valid's multi_logloss: 0.142038
[162]	train's multi_logloss: 0.0936387	valid's multi_logloss: 0.140635
[163]	train's multi_logloss: 0.0921515	valid's multi_logloss: 0.139131
[164]	train's multi_logloss: 0.0906907	valid's multi_logloss: 0.137763
[165]	train's multi_logloss: 0.0892561	valid's multi_logloss: 0.136427
[166]	train's multi_logloss: 0.087843	valid's multi_logloss: 0.135086
[167]	train's multi_logloss: 0.086451	valid's multi_logloss: 0.133739
[168]	train's multi_logloss: 0.0850849	valid's multi_logloss: 0.132369
[169]	train's multi_logloss: 0.083762	valid's multi_logloss: 0.131092
[170]	train's multi_logloss: 0.0824467	valid's multi_logloss: 0.129783
[171]	train's multi_logloss: 0.0811427	valid's multi_logloss: 0.128501
[172]	train's multi_logloss: 0.0798664	valid's multi_logloss: 0.127302
[173]	train's multi_logloss: 0.0786061	valid's multi_logloss: 0.126063
[174]	train's multi_logloss: 0.0773618	valid's multi_logloss: 0.12487
[175]	train's multi_logloss: 0.0761391	valid's multi_logloss: 0.123772
[176]	train's multi_logloss: 0.0749324	valid's multi_logloss: 0.122579
[177]	train's multi_logloss: 0.0737498	valid's multi_logloss: 0.121433
[178]	train's multi_logloss: 0.0725959	valid's multi_logloss: 0.120319
[179]	train's multi_logloss: 0.0714604	valid's multi_logloss: 0.119216
[180]	train's multi_logloss: 0.0703318	valid's multi_logloss: 0.118091
[181]	train's multi_logloss: 0.0692215	valid's multi_logloss: 0.117009
[182]	train's multi_logloss: 0.0681297	valid's multi_logloss: 0.115897
[183]	train's multi_logloss: 0.0670548	valid's multi_logloss: 0.114867
[184]	train's multi_logloss: 0.0659969	valid's multi_logloss: 0.113798
[185]	train's multi_logloss: 0.0649595	valid's multi_logloss: 0.112779
[186]	train's multi_logloss: 0.0639332	valid's multi_logloss: 0.111709
[187]	train's multi_logloss: 0.0629409	valid's multi_logloss: 0.110721
[188]	train's multi_logloss: 0.0619619	valid's multi_logloss: 0.10981
[189]	train's multi_logloss: 0.060988	valid's multi_logloss: 0.108928
[190]	train's multi_logloss: 0.0600282	valid's multi_logloss: 0.107971
[191]	train's multi_logloss: 0.0590926	valid's multi_logloss: 0.107053
[192]	train's multi_logloss: 0.0581623	valid's multi_logloss: 0.10614
[193]	train's multi_logloss: 0.0572531	valid's multi_logloss: 0.105236
[194]	train's multi_logloss: 0.0563718	valid's multi_logloss: 0.104396
[195]	train's multi_logloss: 0.0554964	valid's multi_logloss: 0.103505
[196]	train's multi_logloss: 0.0546258	valid's multi_logloss: 0.102649
[197]	train's multi_logloss: 0.0537659	valid's multi_logloss: 0.101841
[198]	train's multi_logloss: 0.0529198	valid's multi_logloss: 0.101028
[199]	train's multi_logloss: 0.0520964	valid's multi_logloss: 0.100202
[200]	train's multi_logloss: 0.0512769	valid's multi_logloss: 0.0994468
[201]	train's multi_logloss: 0.0504801	valid's multi_logloss: 0.0986739
[202]	train's multi_logloss: 0.0496866	valid's multi_logloss: 0.0979203
[203]	train's multi_logloss: 0.048903	valid's multi_logloss: 0.097158
[204]	train's multi_logloss: 0.0481359	valid's multi_logloss: 0.0964148
[205]	train's multi_logloss: 0.0473834	valid's multi_logloss: 0.0956742
[206]	train's multi_logloss: 0.0466369	valid's multi_logloss: 0.0948875
[207]	train's multi_logloss: 0.0459077	valid's multi_logloss: 0.0941628
[208]	train's multi_logloss: 0.0451939	valid's multi_logloss: 0.0935072
[209]	train's multi_logloss: 0.0444808	valid's multi_logloss: 0.0928327
[210]	train's multi_logloss: 0.0437787	valid's multi_logloss: 0.0921458
[211]	train's multi_logloss: 0.0430889	valid's multi_logloss: 0.0915182
[212]	train's multi_logloss: 0.0424231	valid's multi_logloss: 0.0908807
[213]	train's multi_logloss: 0.0417549	valid's multi_logloss: 0.0902309
[214]	train's multi_logloss: 0.0410983	valid's multi_logloss: 0.0896222
[215]	train's multi_logloss: 0.0404575	valid's multi_logloss: 0.0890328
[216]	train's multi_logloss: 0.039823	valid's multi_logloss: 0.088366
[217]	train's multi_logloss: 0.039198	valid's multi_logloss: 0.087767
[218]	train's multi_logloss: 0.0385845	valid's multi_logloss: 0.0871569
[219]	train's multi_logloss: 0.037979	valid's multi_logloss: 0.0865888
[220]	train's multi_logloss: 0.0373793	valid's multi_logloss: 0.08605
[221]	train's multi_logloss: 0.0367919	valid's multi_logloss: 0.0854995
[222]	train's multi_logloss: 0.0362161	valid's multi_logloss: 0.0850081
[223]	train's multi_logloss: 0.0356463	valid's multi_logloss: 0.0845066
[224]	train's multi_logloss: 0.0350886	valid's multi_logloss: 0.0840454
[225]	train's multi_logloss: 0.0345368	valid's multi_logloss: 0.0835344
[226]	train's multi_logloss: 0.0339945	valid's multi_logloss: 0.0830662
[227]	train's multi_logloss: 0.0334664	valid's multi_logloss: 0.0825708
[228]	train's multi_logloss: 0.0329441	valid's multi_logloss: 0.0821276
[229]	train's multi_logloss: 0.0324284	valid's multi_logloss: 0.0816882
[230]	train's multi_logloss: 0.0319214	valid's multi_logloss: 0.0812508
[231]	train's multi_logloss: 0.031425	valid's multi_logloss: 0.0808319
[232]	train's multi_logloss: 0.030932	valid's multi_logloss: 0.0803938
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[234]	train's multi_logloss: 0.0299692	valid's multi_logloss: 0.0795677
[235]	train's multi_logloss: 0.0295011	valid's multi_logloss: 0.0791731
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[237]	train's multi_logloss: 0.0285929	valid's multi_logloss: 0.0783344
[238]	train's multi_logloss: 0.0281516	valid's multi_logloss: 0.0779249
[239]	train's multi_logloss: 0.027711	valid's multi_logloss: 0.0775226
[240]	train's multi_logloss: 0.027281	valid's multi_logloss: 0.0771181
[241]	train's multi_logloss: 0.0268524	valid's multi_logloss: 0.0767578
[242]	train's multi_logloss: 0.0264338	valid's multi_logloss: 0.0764072
[243]	train's multi_logloss: 0.0260212	valid's multi_logloss: 0.0760528
[244]	train's multi_logloss: 0.0256162	valid's multi_logloss: 0.0757035
[245]	train's multi_logloss: 0.02522	valid's multi_logloss: 0.0753491
[246]	train's multi_logloss: 0.0248243	valid's multi_logloss: 0.0750546
[247]	train's multi_logloss: 0.0244357	valid's multi_logloss: 0.0747386
[248]	train's multi_logloss: 0.0240542	valid's multi_logloss: 0.0744171
[249]	train's multi_logloss: 0.0236786	valid's multi_logloss: 0.0741085
[250]	train's multi_logloss: 0.0233092	valid's multi_logloss: 0.0738058
[251]	train's multi_logloss: 0.0229457	valid's multi_logloss: 0.0734558
[252]	train's multi_logloss: 0.0225878	valid's multi_logloss: 0.0731773
[253]	train's multi_logloss: 0.0222395	valid's multi_logloss: 0.0729395
[254]	train's multi_logloss: 0.0218981	valid's multi_logloss: 0.0727085
[255]	train's multi_logloss: 0.0215577	valid's multi_logloss: 0.0724686
[256]	train's multi_logloss: 0.0212242	valid's multi_logloss: 0.0722067
[257]	train's multi_logloss: 0.0208983	valid's multi_logloss: 0.0719578
[258]	train's multi_logloss: 0.0205767	valid's multi_logloss: 0.071738
[259]	train's multi_logloss: 0.0202599	valid's multi_logloss: 0.0715151
[260]	train's multi_logloss: 0.0199429	valid's multi_logloss: 0.0712735
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[625]	train's multi_logloss: 9.01446e-05	valid's multi_logloss: 0.0881107
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[720]	train's multi_logloss: 2.58158e-05	valid's multi_logloss: 0.0991179
[721]	train's multi_logloss: 2.54528e-05	valid's multi_logloss: 0.0991523
[722]	train's multi_logloss: 2.51101e-05	valid's multi_logloss: 0.0992721
[723]	train's multi_logloss: 2.47982e-05	valid's multi_logloss: 0.0993385
[724]	train's multi_logloss: 2.45017e-05	valid's multi_logloss: 0.0994831
[725]	train's multi_logloss: 2.42306e-05	valid's multi_logloss: 0.0995716
[726]	train's multi_logloss: 2.39317e-05	valid's multi_logloss: 0.099707
[727]	train's multi_logloss: 2.36282e-05	valid's multi_logloss: 0.0997654
[728]	train's multi_logloss: 2.33317e-05	valid's multi_logloss: 0.0998713
[729]	train's multi_logloss: 2.30521e-05	valid's multi_logloss: 0.0999914
[730]	train's multi_logloss: 2.27685e-05	valid's multi_logloss: 0.100104
[731]	train's multi_logloss: 2.24811e-05	valid's multi_logloss: 0.100178
[732]	train's multi_logloss: 2.22139e-05	valid's multi_logloss: 0.100295
[733]	train's multi_logloss: 2.19726e-05	valid's multi_logloss: 0.100353
[734]	train's multi_logloss: 2.17266e-05	valid's multi_logloss: 0.100374
[735]	train's multi_logloss: 2.14702e-05	valid's multi_logloss: 0.100471
[736]	train's multi_logloss: 2.12333e-05	valid's multi_logloss: 0.100587
[737]	train's multi_logloss: 2.09754e-05	valid's multi_logloss: 0.100692
[738]	train's multi_logloss: 2.07232e-05	valid's multi_logloss: 0.100787
[739]	train's multi_logloss: 2.04557e-05	valid's multi_logloss: 0.100928
[740]	train's multi_logloss: 2.02232e-05	valid's multi_logloss: 0.100972
[741]	train's multi_logloss: 1.99676e-05	valid's multi_logloss: 0.101108
[742]	train's multi_logloss: 1.97241e-05	valid's multi_logloss: 0.101151
[743]	train's multi_logloss: 1.94506e-05	valid's multi_logloss: 0.101232
[744]	train's multi_logloss: 1.92096e-05	valid's multi_logloss: 0.101351
[745]	train's multi_logloss: 1.89966e-05	valid's multi_logloss: 0.101494
[746]	train's multi_logloss: 1.87617e-05	valid's multi_logloss: 0.101605
[747]	train's multi_logloss: 1.85028e-05	valid's multi_logloss: 0.101746
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[748]	train's multi_logloss: 1.82808e-05	valid's multi_logloss: 0.101842
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[749]	train's multi_logloss: 1.80809e-05	valid's multi_logloss: 0.10198
[750]	train's multi_logloss: 1.78762e-05	valid's multi_logloss: 0.10211
[751]	train's multi_logloss: 1.7662e-05	valid's multi_logloss: 0.102155
[752]	train's multi_logloss: 1.74388e-05	valid's multi_logloss: 0.102237
[753]	train's multi_logloss: 1.72353e-05	valid's multi_logloss: 0.102357
[754]	train's multi_logloss: 1.70373e-05	valid's multi_logloss: 0.102494
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[755]	train's multi_logloss: 1.68403e-05	valid's multi_logloss: 0.10262
[756]	train's multi_logloss: 1.66282e-05	valid's multi_logloss: 0.102737
[757]	train's multi_logloss: 1.64343e-05	valid's multi_logloss: 0.10283
[758]	train's multi_logloss: 1.62322e-05	valid's multi_logloss: 0.102936
[759]	train's multi_logloss: 1.60539e-05	valid's multi_logloss: 0.102972
[760]	train's multi_logloss: 1.58753e-05	valid's multi_logloss: 0.103107
[761]	train's multi_logloss: 1.56683e-05	valid's multi_logloss: 0.103206
[762]	train's multi_logloss: 1.55081e-05	valid's multi_logloss: 0.103338
[763]	train's multi_logloss: 1.53262e-05	valid's multi_logloss: 0.10344
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[764]	train's multi_logloss: 1.51639e-05	valid's multi_logloss: 0.103544
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[765]	train's multi_logloss: 1.49584e-05	valid's multi_logloss: 0.103659
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[766]	train's multi_logloss: 1.47541e-05	valid's multi_logloss: 0.103784
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[767]	train's multi_logloss: 1.45842e-05	valid's multi_logloss: 0.103912
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[768]	train's multi_logloss: 1.4402e-05	valid's multi_logloss: 0.103983
[769]	train's multi_logloss: 1.42417e-05	valid's multi_logloss: 0.104109
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[770]	train's multi_logloss: 1.40681e-05	valid's multi_logloss: 0.104237
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[771]	train's multi_logloss: 1.39018e-05	valid's multi_logloss: 0.10431
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[772]	train's multi_logloss: 1.37155e-05	valid's multi_logloss: 0.104455
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[773]	train's multi_logloss: 1.35554e-05	valid's multi_logloss: 0.104559
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[774]	train's multi_logloss: 1.3376e-05	valid's multi_logloss: 0.104684
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[775]	train's multi_logloss: 1.31948e-05	valid's multi_logloss: 0.104789
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[776]	train's multi_logloss: 1.30423e-05	valid's multi_logloss: 0.104908
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[777]	train's multi_logloss: 1.28782e-05	valid's multi_logloss: 0.104968
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[778]	train's multi_logloss: 1.27259e-05	valid's multi_logloss: 0.105084
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[779]	train's multi_logloss: 1.25744e-05	valid's multi_logloss: 0.105181
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[780]	train's multi_logloss: 1.24241e-05	valid's multi_logloss: 0.105287
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[781]	train's multi_logloss: 1.22667e-05	valid's multi_logloss: 0.105369
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[782]	train's multi_logloss: 1.21134e-05	valid's multi_logloss: 0.105455
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[783]	train's multi_logloss: 1.19833e-05	valid's multi_logloss: 0.105556
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[784]	train's multi_logloss: 1.18497e-05	valid's multi_logloss: 0.105618
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[785]	train's multi_logloss: 1.16986e-05	valid's multi_logloss: 0.105698
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[786]	train's multi_logloss: 1.15348e-05	valid's multi_logloss: 0.105809
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[787]	train's multi_logloss: 1.13797e-05	valid's multi_logloss: 0.105936
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[788]	train's multi_logloss: 1.12327e-05	valid's multi_logloss: 0.106029
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[789]	train's multi_logloss: 1.10988e-05	valid's multi_logloss: 0.10616
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[790]	train's multi_logloss: 1.09707e-05	valid's multi_logloss: 0.106259
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[791]	train's multi_logloss: 1.08297e-05	valid's multi_logloss: 0.106332
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[792]	train's multi_logloss: 1.06964e-05	valid's multi_logloss: 0.106436
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[793]	train's multi_logloss: 1.05706e-05	valid's multi_logloss: 0.106561
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[794]	train's multi_logloss: 1.0446e-05	valid's multi_logloss: 0.106635
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[795]	train's multi_logloss: 1.03089e-05	valid's multi_logloss: 0.10668
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[796]	train's multi_logloss: 1.01735e-05	valid's multi_logloss: 0.106777
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[797]	train's multi_logloss: 1.0031e-05	valid's multi_logloss: 0.106884
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[798]	train's multi_logloss: 9.89413e-06	valid's multi_logloss: 0.106945
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[799]	train's multi_logloss: 9.76243e-06	valid's multi_logloss: 0.107061
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[800]	train's multi_logloss: 9.63475e-06	valid's multi_logloss: 0.107129
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[801]	train's multi_logloss: 9.52203e-06	valid's multi_logloss: 0.107188
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[802]	train's multi_logloss: 9.39022e-06	valid's multi_logloss: 0.107308
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[803]	train's multi_logloss: 9.26131e-06	valid's multi_logloss: 0.107385
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[804]	train's multi_logloss: 9.13388e-06	valid's multi_logloss: 0.107466
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[805]	train's multi_logloss: 9.00805e-06	valid's multi_logloss: 0.107548
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[806]	train's multi_logloss: 8.90347e-06	valid's multi_logloss: 0.107608
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[807]	train's multi_logloss: 8.78141e-06	valid's multi_logloss: 0.107694
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[808]	train's multi_logloss: 8.66171e-06	valid's multi_logloss: 0.107787
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[809]	train's multi_logloss: 8.54463e-06	valid's multi_logloss: 0.107827
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[810]	train's multi_logloss: 8.42993e-06	valid's multi_logloss: 0.107934
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[811]	train's multi_logloss: 8.33865e-06	valid's multi_logloss: 0.107998
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[812]	train's multi_logloss: 8.23619e-06	valid's multi_logloss: 0.108067
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[813]	train's multi_logloss: 8.12381e-06	valid's multi_logloss: 0.108167
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[814]	train's multi_logloss: 8.03904e-06	valid's multi_logloss: 0.108258
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[815]	train's multi_logloss: 7.94301e-06	valid's multi_logloss: 0.108338
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[816]	train's multi_logloss: 7.85165e-06	valid's multi_logloss: 0.108424
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[817]	train's multi_logloss: 7.74852e-06	valid's multi_logloss: 0.108527
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[818]	train's multi_logloss: 7.65936e-06	valid's multi_logloss: 0.108624
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[819]	train's multi_logloss: 7.56021e-06	valid's multi_logloss: 0.108742
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[820]	train's multi_logloss: 7.48718e-06	valid's multi_logloss: 0.108845
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[821]	train's multi_logloss: 7.41147e-06	valid's multi_logloss: 0.108931
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[822]	train's multi_logloss: 7.3208e-06	valid's multi_logloss: 0.109041
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[823]	train's multi_logloss: 7.24222e-06	valid's multi_logloss: 0.109164
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[824]	train's multi_logloss: 7.17952e-06	valid's multi_logloss: 0.109253
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[825]	train's multi_logloss: 7.0833e-06	valid's multi_logloss: 0.109363
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[826]	train's multi_logloss: 7.00176e-06	valid's multi_logloss: 0.109447
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[827]	train's multi_logloss: 6.9138e-06	valid's multi_logloss: 0.109552
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[828]	train's multi_logloss: 6.81791e-06	valid's multi_logloss: 0.109639
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[829]	train's multi_logloss: 6.73755e-06	valid's multi_logloss: 0.109772
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[830]	train's multi_logloss: 6.66266e-06	valid's multi_logloss: 0.109882
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[831]	train's multi_logloss: 6.59151e-06	valid's multi_logloss: 0.109955
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[832]	train's multi_logloss: 6.53176e-06	valid's multi_logloss: 0.110037
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[833]	train's multi_logloss: 6.46287e-06	valid's multi_logloss: 0.110125
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[834]	train's multi_logloss: 6.38889e-06	valid's multi_logloss: 0.110226
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[835]	train's multi_logloss: 6.31732e-06	valid's multi_logloss: 0.110301
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[836]	train's multi_logloss: 6.25036e-06	valid's multi_logloss: 0.110401
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[837]	train's multi_logloss: 6.20148e-06	valid's multi_logloss: 0.110501
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[838]	train's multi_logloss: 6.12783e-06	valid's multi_logloss: 0.110598
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[839]	train's multi_logloss: 6.05118e-06	valid's multi_logloss: 0.110645
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[840]	train's multi_logloss: 5.96952e-06	valid's multi_logloss: 0.110725
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[841]	train's multi_logloss: 5.9043e-06	valid's multi_logloss: 0.110799
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[842]	train's multi_logloss: 5.82746e-06	valid's multi_logloss: 0.110884
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[843]	train's multi_logloss: 5.7647e-06	valid's multi_logloss: 0.110934
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[844]	train's multi_logloss: 5.6915e-06	valid's multi_logloss: 0.110965
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[845]	train's multi_logloss: 5.62607e-06	valid's multi_logloss: 0.111047
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[846]	train's multi_logloss: 5.56699e-06	valid's multi_logloss: 0.111145
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[847]	train's multi_logloss: 5.49387e-06	valid's multi_logloss: 0.111218
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[848]	train's multi_logloss: 5.42576e-06	valid's multi_logloss: 0.111281
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[849]	train's multi_logloss: 5.35832e-06	valid's multi_logloss: 0.111359
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[850]	train's multi_logloss: 5.29347e-06	valid's multi_logloss: 0.111411
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[851]	train's multi_logloss: 5.22707e-06	valid's multi_logloss: 0.111505
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[852]	train's multi_logloss: 5.17183e-06	valid's multi_logloss: 0.111588
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[853]	train's multi_logloss: 5.1199e-06	valid's multi_logloss: 0.11167
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[854]	train's multi_logloss: 5.05368e-06	valid's multi_logloss: 0.111761
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[855]	train's multi_logloss: 4.99299e-06	valid's multi_logloss: 0.111835
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[856]	train's multi_logloss: 4.93449e-06	valid's multi_logloss: 0.111908
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[857]	train's multi_logloss: 4.88967e-06	valid's multi_logloss: 0.111991
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[858]	train's multi_logloss: 4.8391e-06	valid's multi_logloss: 0.112085
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[859]	train's multi_logloss: 4.78841e-06	valid's multi_logloss: 0.11213
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[860]	train's multi_logloss: 4.73929e-06	valid's multi_logloss: 0.11224
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[861]	train's multi_logloss: 4.67856e-06	valid's multi_logloss: 0.112284
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[862]	train's multi_logloss: 4.61982e-06	valid's multi_logloss: 0.112393
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[863]	train's multi_logloss: 4.56163e-06	valid's multi_logloss: 0.112418
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[864]	train's multi_logloss: 4.51166e-06	valid's multi_logloss: 0.112479
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[865]	train's multi_logloss: 4.46516e-06	valid's multi_logloss: 0.11251
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[866]	train's multi_logloss: 4.42325e-06	valid's multi_logloss: 0.112586
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[867]	train's multi_logloss: 4.36894e-06	valid's multi_logloss: 0.11269
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[868]	train's multi_logloss: 4.32354e-06	valid's multi_logloss: 0.112785
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[869]	train's multi_logloss: 4.28067e-06	valid's multi_logloss: 0.112878
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[870]	train's multi_logloss: 4.23655e-06	valid's multi_logloss: 0.112974
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[871]	train's multi_logloss: 4.19187e-06	valid's multi_logloss: 0.113066
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[872]	train's multi_logloss: 4.14701e-06	valid's multi_logloss: 0.113115
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[873]	train's multi_logloss: 4.11032e-06	valid's multi_logloss: 0.113165
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[874]	train's multi_logloss: 4.06906e-06	valid's multi_logloss: 0.113288
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[875]	train's multi_logloss: 4.01809e-06	valid's multi_logloss: 0.113305
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[876]	train's multi_logloss: 3.97498e-06	valid's multi_logloss: 0.113395
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[877]	train's multi_logloss: 3.93177e-06	valid's multi_logloss: 0.113454
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[878]	train's multi_logloss: 3.88615e-06	valid's multi_logloss: 0.113584
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[879]	train's multi_logloss: 3.84448e-06	valid's multi_logloss: 0.113685
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[880]	train's multi_logloss: 3.7954e-06	valid's multi_logloss: 0.113797
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[881]	train's multi_logloss: 3.74791e-06	valid's multi_logloss: 0.113914
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[882]	train's multi_logloss: 3.70216e-06	valid's multi_logloss: 0.114007
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[883]	train's multi_logloss: 3.6575e-06	valid's multi_logloss: 0.114099
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[884]	train's multi_logloss: 3.61671e-06	valid's multi_logloss: 0.114199
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[885]	train's multi_logloss: 3.58439e-06	valid's multi_logloss: 0.114258
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[886]	train's multi_logloss: 3.55246e-06	valid's multi_logloss: 0.114368
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[887]	train's multi_logloss: 3.51588e-06	valid's multi_logloss: 0.114469
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[888]	train's multi_logloss: 3.47147e-06	valid's multi_logloss: 0.114571
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[889]	train's multi_logloss: 3.43384e-06	valid's multi_logloss: 0.114639
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[890]	train's multi_logloss: 3.39766e-06	valid's multi_logloss: 0.11474
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[891]	train's multi_logloss: 3.35872e-06	valid's multi_logloss: 0.114864
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[892]	train's multi_logloss: 3.32803e-06	valid's multi_logloss: 0.114994
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[893]	train's multi_logloss: 3.30076e-06	valid's multi_logloss: 0.115071
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[894]	train's multi_logloss: 3.26961e-06	valid's multi_logloss: 0.115181
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[895]	train's multi_logloss: 3.2412e-06	valid's multi_logloss: 0.115268
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[896]	train's multi_logloss: 3.20824e-06	valid's multi_logloss: 0.115343
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[897]	train's multi_logloss: 3.17953e-06	valid's multi_logloss: 0.11539
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[898]	train's multi_logloss: 3.14828e-06	valid's multi_logloss: 0.115467
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[899]	train's multi_logloss: 3.11476e-06	valid's multi_logloss: 0.115556
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[900]	train's multi_logloss: 3.08103e-06	valid's multi_logloss: 0.115597
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[901]	train's multi_logloss: 3.04671e-06	valid's multi_logloss: 0.115677
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[902]	train's multi_logloss: 3.01014e-06	valid's multi_logloss: 0.115796
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[903]	train's multi_logloss: 2.98182e-06	valid's multi_logloss: 0.11589
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[904]	train's multi_logloss: 2.96177e-06	valid's multi_logloss: 0.115914
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[905]	train's multi_logloss: 2.92856e-06	valid's multi_logloss: 0.115956
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[906]	train's multi_logloss: 2.90318e-06	valid's multi_logloss: 0.116051
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[907]	train's multi_logloss: 2.87522e-06	valid's multi_logloss: 0.116142
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[908]	train's multi_logloss: 2.84758e-06	valid's multi_logloss: 0.116263
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[909]	train's multi_logloss: 2.81714e-06	valid's multi_logloss: 0.11638
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[910]	train's multi_logloss: 2.79032e-06	valid's multi_logloss: 0.116484
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[911]	train's multi_logloss: 2.76346e-06	valid's multi_logloss: 0.116566
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[912]	train's multi_logloss: 2.73466e-06	valid's multi_logloss: 0.116661
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[913]	train's multi_logloss: 2.70469e-06	valid's multi_logloss: 0.116761
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[914]	train's multi_logloss: 2.68401e-06	valid's multi_logloss: 0.116854
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[915]	train's multi_logloss: 2.66249e-06	valid's multi_logloss: 0.116928
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[916]	train's multi_logloss: 2.6319e-06	valid's multi_logloss: 0.11699
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[917]	train's multi_logloss: 2.60227e-06	valid's multi_logloss: 0.11703
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[918]	train's multi_logloss: 2.57383e-06	valid's multi_logloss: 0.117124
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[919]	train's multi_logloss: 2.54717e-06	valid's multi_logloss: 0.117203
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[920]	train's multi_logloss: 2.52197e-06	valid's multi_logloss: 0.117263
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[921]	train's multi_logloss: 2.48959e-06	valid's multi_logloss: 0.117366
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[922]	train's multi_logloss: 2.45929e-06	valid's multi_logloss: 0.117471
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[923]	train's multi_logloss: 2.44174e-06	valid's multi_logloss: 0.11753
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[924]	train's multi_logloss: 2.41727e-06	valid's multi_logloss: 0.117605
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[925]	train's multi_logloss: 2.39827e-06	valid's multi_logloss: 0.117664
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[926]	train's multi_logloss: 2.36895e-06	valid's multi_logloss: 0.117761
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[927]	train's multi_logloss: 2.34767e-06	valid's multi_logloss: 0.117827
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[928]	train's multi_logloss: 2.32036e-06	valid's multi_logloss: 0.117926
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[929]	train's multi_logloss: 2.2962e-06	valid's multi_logloss: 0.118017
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[930]	train's multi_logloss: 2.27158e-06	valid's multi_logloss: 0.118079
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[931]	train's multi_logloss: 2.24718e-06	valid's multi_logloss: 0.118172
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[932]	train's multi_logloss: 2.22347e-06	valid's multi_logloss: 0.11823
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[933]	train's multi_logloss: 2.20102e-06	valid's multi_logloss: 0.118297
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[934]	train's multi_logloss: 2.18311e-06	valid's multi_logloss: 0.118369
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[935]	train's multi_logloss: 2.16126e-06	valid's multi_logloss: 0.118434
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[936]	train's multi_logloss: 2.146e-06	valid's multi_logloss: 0.118534
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[937]	train's multi_logloss: 2.12483e-06	valid's multi_logloss: 0.11859
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[938]	train's multi_logloss: 2.10156e-06	valid's multi_logloss: 0.118669
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[939]	train's multi_logloss: 2.08273e-06	valid's multi_logloss: 0.118714
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[940]	train's multi_logloss: 2.06595e-06	valid's multi_logloss: 0.118789
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[941]	train's multi_logloss: 2.04844e-06	valid's multi_logloss: 0.118838
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[942]	train's multi_logloss: 2.0272e-06	valid's multi_logloss: 0.118878
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[943]	train's multi_logloss: 2.00737e-06	valid's multi_logloss: 0.118932
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[944]	train's multi_logloss: 1.98775e-06	valid's multi_logloss: 0.118992
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[945]	train's multi_logloss: 1.96929e-06	valid's multi_logloss: 0.119049
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[946]	train's multi_logloss: 1.94983e-06	valid's multi_logloss: 0.119114
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[947]	train's multi_logloss: 1.9333e-06	valid's multi_logloss: 0.119203
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[948]	train's multi_logloss: 1.91368e-06	valid's multi_logloss: 0.119263
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[949]	train's multi_logloss: 1.88892e-06	valid's multi_logloss: 0.119363
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[950]	train's multi_logloss: 1.87266e-06	valid's multi_logloss: 0.119437
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[951]	train's multi_logloss: 1.85182e-06	valid's multi_logloss: 0.119542
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[952]	train's multi_logloss: 1.83327e-06	valid's multi_logloss: 0.119613
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[953]	train's multi_logloss: 1.81755e-06	valid's multi_logloss: 0.119673
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[954]	train's multi_logloss: 1.79814e-06	valid's multi_logloss: 0.119736
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[955]	train's multi_logloss: 1.77825e-06	valid's multi_logloss: 0.119827
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[956]	train's multi_logloss: 1.76237e-06	valid's multi_logloss: 0.119881
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[957]	train's multi_logloss: 1.74607e-06	valid's multi_logloss: 0.119947
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[958]	train's multi_logloss: 1.72579e-06	valid's multi_logloss: 0.119997
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[959]	train's multi_logloss: 1.71137e-06	valid's multi_logloss: 0.120077
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[960]	train's multi_logloss: 1.69409e-06	valid's multi_logloss: 0.120124
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[961]	train's multi_logloss: 1.68344e-06	valid's multi_logloss: 0.120142
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[962]	train's multi_logloss: 1.66695e-06	valid's multi_logloss: 0.120196
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[963]	train's multi_logloss: 1.65122e-06	valid's multi_logloss: 0.120262
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[964]	train's multi_logloss: 1.63756e-06	valid's multi_logloss: 0.120334
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[965]	train's multi_logloss: 1.6273e-06	valid's multi_logloss: 0.120342
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[966]	train's multi_logloss: 1.61144e-06	valid's multi_logloss: 0.120378
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[967]	train's multi_logloss: 1.59667e-06	valid's multi_logloss: 0.120464
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[968]	train's multi_logloss: 1.58276e-06	valid's multi_logloss: 0.120498
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[969]	train's multi_logloss: 1.56819e-06	valid's multi_logloss: 0.120557
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[970]	train's multi_logloss: 1.55291e-06	valid's multi_logloss: 0.120608
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[971]	train's multi_logloss: 1.53626e-06	valid's multi_logloss: 0.120641
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[972]	train's multi_logloss: 1.51816e-06	valid's multi_logloss: 0.120711
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[973]	train's multi_logloss: 1.50285e-06	valid's multi_logloss: 0.120761
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[974]	train's multi_logloss: 1.48841e-06	valid's multi_logloss: 0.120821
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[975]	train's multi_logloss: 1.47679e-06	valid's multi_logloss: 0.120851
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[976]	train's multi_logloss: 1.46335e-06	valid's multi_logloss: 0.12091
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[977]	train's multi_logloss: 1.45068e-06	valid's multi_logloss: 0.120934
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[978]	train's multi_logloss: 1.43397e-06	valid's multi_logloss: 0.12099
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[979]	train's multi_logloss: 1.42085e-06	valid's multi_logloss: 0.121084
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[980]	train's multi_logloss: 1.4082e-06	valid's multi_logloss: 0.121125
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[981]	train's multi_logloss: 1.3928e-06	valid's multi_logloss: 0.121185
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[982]	train's multi_logloss: 1.37901e-06	valid's multi_logloss: 0.121265
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[983]	train's multi_logloss: 1.36641e-06	valid's multi_logloss: 0.121343
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[984]	train's multi_logloss: 1.35223e-06	valid's multi_logloss: 0.121392
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[985]	train's multi_logloss: 1.3364e-06	valid's multi_logloss: 0.121477
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[986]	train's multi_logloss: 1.32518e-06	valid's multi_logloss: 0.121494
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[987]	train's multi_logloss: 1.31167e-06	valid's multi_logloss: 0.121521
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[988]	train's multi_logloss: 1.29909e-06	valid's multi_logloss: 0.121572
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[989]	train's multi_logloss: 1.285e-06	valid's multi_logloss: 0.121589
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[990]	train's multi_logloss: 1.27198e-06	valid's multi_logloss: 0.121682
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[991]	train's multi_logloss: 1.26202e-06	valid's multi_logloss: 0.121698
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[992]	train's multi_logloss: 1.24979e-06	valid's multi_logloss: 0.12178
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[993]	train's multi_logloss: 1.23776e-06	valid's multi_logloss: 0.121845
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[994]	train's multi_logloss: 1.22795e-06	valid's multi_logloss: 0.121868
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[995]	train's multi_logloss: 1.21538e-06	valid's multi_logloss: 0.121962
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[996]	train's multi_logloss: 1.20329e-06	valid's multi_logloss: 0.122018
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[997]	train's multi_logloss: 1.19227e-06	valid's multi_logloss: 0.122095
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[998]	train's multi_logloss: 1.17992e-06	valid's multi_logloss: 0.12214
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[999]	train's multi_logloss: 1.16865e-06	valid's multi_logloss: 0.122201
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1000]	train's multi_logloss: 1.15845e-06	valid's multi_logloss: 0.122254
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1001]	train's multi_logloss: 1.14599e-06	valid's multi_logloss: 0.122322
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1002]	train's multi_logloss: 1.13447e-06	valid's multi_logloss: 0.122407
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1003]	train's multi_logloss: 1.12485e-06	valid's multi_logloss: 0.122449
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1004]	train's multi_logloss: 1.11544e-06	valid's multi_logloss: 0.122481
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1005]	train's multi_logloss: 1.10225e-06	valid's multi_logloss: 0.122586
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1006]	train's multi_logloss: 1.09326e-06	valid's multi_logloss: 0.122608
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1007]	train's multi_logloss: 1.08545e-06	valid's multi_logloss: 0.122627
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1008]	train's multi_logloss: 1.07625e-06	valid's multi_logloss: 0.122722
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1009]	train's multi_logloss: 1.06588e-06	valid's multi_logloss: 0.122741
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1010]	train's multi_logloss: 1.05676e-06	valid's multi_logloss: 0.122808
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1011]	train's multi_logloss: 1.04797e-06	valid's multi_logloss: 0.122844
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1012]	train's multi_logloss: 1.03879e-06	valid's multi_logloss: 0.122884
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1013]	train's multi_logloss: 1.02849e-06	valid's multi_logloss: 0.122968
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1014]	train's multi_logloss: 1.02016e-06	valid's multi_logloss: 0.122996
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1015]	train's multi_logloss: 1.01224e-06	valid's multi_logloss: 0.123037
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1016]	train's multi_logloss: 1.00379e-06	valid's multi_logloss: 0.123094
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1017]	train's multi_logloss: 9.97441e-07	valid's multi_logloss: 0.123149
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1018]	train's multi_logloss: 9.90367e-07	valid's multi_logloss: 0.123194
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1019]	train's multi_logloss: 9.84585e-07	valid's multi_logloss: 0.123232
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1020]	train's multi_logloss: 9.77916e-07	valid's multi_logloss: 0.123296
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1021]	train's multi_logloss: 9.70838e-07	valid's multi_logloss: 0.123347
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1022]	train's multi_logloss: 9.6324e-07	valid's multi_logloss: 0.123405
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1023]	train's multi_logloss: 9.56705e-07	valid's multi_logloss: 0.123465
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1024]	train's multi_logloss: 9.48784e-07	valid's multi_logloss: 0.123497
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1025]	train's multi_logloss: 9.42192e-07	valid's multi_logloss: 0.123544
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1026]	train's multi_logloss: 9.35904e-07	valid's multi_logloss: 0.123593
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1027]	train's multi_logloss: 9.28258e-07	valid's multi_logloss: 0.123656
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1028]	train's multi_logloss: 9.21835e-07	valid's multi_logloss: 0.123717
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1029]	train's multi_logloss: 9.15598e-07	valid's multi_logloss: 0.123762
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1030]	train's multi_logloss: 9.08619e-07	valid's multi_logloss: 0.12383
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1031]	train's multi_logloss: 9.02535e-07	valid's multi_logloss: 0.123871
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1032]	train's multi_logloss: 8.96004e-07	valid's multi_logloss: 0.123917
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1033]	train's multi_logloss: 8.88252e-07	valid's multi_logloss: 0.123991
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1034]	train's multi_logloss: 8.80329e-07	valid's multi_logloss: 0.124059
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1035]	train's multi_logloss: 8.74288e-07	valid's multi_logloss: 0.12412
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1036]	train's multi_logloss: 8.68342e-07	valid's multi_logloss: 0.12415
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1037]	train's multi_logloss: 8.62919e-07	valid's multi_logloss: 0.124201
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1038]	train's multi_logloss: 8.569e-07	valid's multi_logloss: 0.124253
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1039]	train's multi_logloss: 8.49718e-07	valid's multi_logloss: 0.124289
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1040]	train's multi_logloss: 8.4369e-07	valid's multi_logloss: 0.124328
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1041]	train's multi_logloss: 8.37338e-07	valid's multi_logloss: 0.124359
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1042]	train's multi_logloss: 8.30234e-07	valid's multi_logloss: 0.124402
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1043]	train's multi_logloss: 8.23608e-07	valid's multi_logloss: 0.124411
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1044]	train's multi_logloss: 8.16866e-07	valid's multi_logloss: 0.124451
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1045]	train's multi_logloss: 8.11519e-07	valid's multi_logloss: 0.12447
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1046]	train's multi_logloss: 8.0571e-07	valid's multi_logloss: 0.124531
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1047]	train's multi_logloss: 8.00339e-07	valid's multi_logloss: 0.124558
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1048]	train's multi_logloss: 7.93799e-07	valid's multi_logloss: 0.124589
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1049]	train's multi_logloss: 7.87739e-07	valid's multi_logloss: 0.124646
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1050]	train's multi_logloss: 7.82921e-07	valid's multi_logloss: 0.124696
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1051]	train's multi_logloss: 7.78138e-07	valid's multi_logloss: 0.124726
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1052]	train's multi_logloss: 7.72457e-07	valid's multi_logloss: 0.124754
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1053]	train's multi_logloss: 7.66928e-07	valid's multi_logloss: 0.124793
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1054]	train's multi_logloss: 7.61964e-07	valid's multi_logloss: 0.124822
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1055]	train's multi_logloss: 7.56293e-07	valid's multi_logloss: 0.124857
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1056]	train's multi_logloss: 7.50848e-07	valid's multi_logloss: 0.12491
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1057]	train's multi_logloss: 7.46249e-07	valid's multi_logloss: 0.124924
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1058]	train's multi_logloss: 7.41439e-07	valid's multi_logloss: 0.124937
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1059]	train's multi_logloss: 7.36293e-07	valid's multi_logloss: 0.124974
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1060]	train's multi_logloss: 7.31075e-07	valid's multi_logloss: 0.124991
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1061]	train's multi_logloss: 7.27495e-07	valid's multi_logloss: 0.125
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1062]	train's multi_logloss: 7.22367e-07	valid's multi_logloss: 0.125043
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1063]	train's multi_logloss: 7.18533e-07	valid's multi_logloss: 0.125051
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1064]	train's multi_logloss: 7.13387e-07	valid's multi_logloss: 0.125084
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1065]	train's multi_logloss: 7.09102e-07	valid's multi_logloss: 0.125117
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1066]	train's multi_logloss: 7.04455e-07	valid's multi_logloss: 0.125145
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1067]	train's multi_logloss: 6.99694e-07	valid's multi_logloss: 0.125179
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1068]	train's multi_logloss: 6.96314e-07	valid's multi_logloss: 0.125201
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1069]	train's multi_logloss: 6.93127e-07	valid's multi_logloss: 0.125228
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1070]	train's multi_logloss: 6.88795e-07	valid's multi_logloss: 0.12526
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1071]	train's multi_logloss: 6.8449e-07	valid's multi_logloss: 0.125291
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1072]	train's multi_logloss: 6.81194e-07	valid's multi_logloss: 0.125316
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1073]	train's multi_logloss: 6.78899e-07	valid's multi_logloss: 0.125322
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1074]	train's multi_logloss: 6.75096e-07	valid's multi_logloss: 0.125331
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1075]	train's multi_logloss: 6.71746e-07	valid's multi_logloss: 0.125328
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1076]	train's multi_logloss: 6.68975e-07	valid's multi_logloss: 0.125333
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1077]	train's multi_logloss: 6.65461e-07	valid's multi_logloss: 0.125336
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1078]	train's multi_logloss: 6.63561e-07	valid's multi_logloss: 0.125338
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1079]	train's multi_logloss: 6.6049e-07	valid's multi_logloss: 0.125324
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1080]	train's multi_logloss: 6.57173e-07	valid's multi_logloss: 0.125314
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1081]	train's multi_logloss: 6.54003e-07	valid's multi_logloss: 0.125324
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1082]	train's multi_logloss: 6.51226e-07	valid's multi_logloss: 0.125327
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1083]	train's multi_logloss: 6.4766e-07	valid's multi_logloss: 0.125317
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1084]	train's multi_logloss: 6.44434e-07	valid's multi_logloss: 0.125326
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1085]	train's multi_logloss: 6.41797e-07	valid's multi_logloss: 0.125299
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1086]	train's multi_logloss: 6.38474e-07	valid's multi_logloss: 0.125289
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1087]	train's multi_logloss: 6.35859e-07	valid's multi_logloss: 0.125275
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1088]	train's multi_logloss: 6.33307e-07	valid's multi_logloss: 0.12526
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1089]	train's multi_logloss: 6.30833e-07	valid's multi_logloss: 0.125284
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1090]	train's multi_logloss: 6.28334e-07	valid's multi_logloss: 0.125281
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1091]	train's multi_logloss: 6.26247e-07	valid's multi_logloss: 0.125266
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1092]	train's multi_logloss: 6.23052e-07	valid's multi_logloss: 0.125255
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1093]	train's multi_logloss: 6.19624e-07	valid's multi_logloss: 0.125255
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1094]	train's multi_logloss: 6.17162e-07	valid's multi_logloss: 0.12524
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1095]	train's multi_logloss: 6.14417e-07	valid's multi_logloss: 0.125265
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1096]	train's multi_logloss: 6.11877e-07	valid's multi_logloss: 0.125252
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1097]	train's multi_logloss: 6.09925e-07	valid's multi_logloss: 0.125228
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1098]	train's multi_logloss: 6.07701e-07	valid's multi_logloss: 0.125231
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1099]	train's multi_logloss: 6.05914e-07	valid's multi_logloss: 0.125232
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1100]	train's multi_logloss: 6.03694e-07	valid's multi_logloss: 0.125219
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1101]	train's multi_logloss: 6.01111e-07	valid's multi_logloss: 0.125218
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1102]	train's multi_logloss: 5.9926e-07	valid's multi_logloss: 0.12522
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1103]	train's multi_logloss: 5.96743e-07	valid's multi_logloss: 0.125215
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1104]	train's multi_logloss: 5.93889e-07	valid's multi_logloss: 0.125234
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1105]	train's multi_logloss: 5.9121e-07	valid's multi_logloss: 0.12523
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1106]	train's multi_logloss: 5.89224e-07	valid's multi_logloss: 0.125212
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1107]	train's multi_logloss: 5.86747e-07	valid's multi_logloss: 0.125217
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1108]	train's multi_logloss: 5.84339e-07	valid's multi_logloss: 0.125208
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1109]	train's multi_logloss: 5.82366e-07	valid's multi_logloss: 0.125192
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1110]	train's multi_logloss: 5.79922e-07	valid's multi_logloss: 0.125213
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1111]	train's multi_logloss: 5.78058e-07	valid's multi_logloss: 0.125216
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1112]	train's multi_logloss: 5.75581e-07	valid's multi_logloss: 0.125212
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1113]	train's multi_logloss: 5.73484e-07	valid's multi_logloss: 0.125199
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1114]	train's multi_logloss: 5.71583e-07	valid's multi_logloss: 0.125209
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1115]	train's multi_logloss: 5.69584e-07	valid's multi_logloss: 0.125203
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1116]	train's multi_logloss: 5.68126e-07	valid's multi_logloss: 0.125195
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1117]	train's multi_logloss: 5.66135e-07	valid's multi_logloss: 0.125203
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1118]	train's multi_logloss: 5.64405e-07	valid's multi_logloss: 0.125192
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1119]	train's multi_logloss: 5.62656e-07	valid's multi_logloss: 0.125219
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1120]	train's multi_logloss: 5.60952e-07	valid's multi_logloss: 0.125207
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1121]	train's multi_logloss: 5.58874e-07	valid's multi_logloss: 0.125196
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1122]	train's multi_logloss: 5.57128e-07	valid's multi_logloss: 0.125202
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1123]	train's multi_logloss: 5.54715e-07	valid's multi_logloss: 0.12522
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1124]	train's multi_logloss: 5.53521e-07	valid's multi_logloss: 0.125207
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1125]	train's multi_logloss: 5.52267e-07	valid's multi_logloss: 0.125203
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1126]	train's multi_logloss: 5.50876e-07	valid's multi_logloss: 0.125192
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1127]	train's multi_logloss: 5.49719e-07	valid's multi_logloss: 0.125199
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1128]	train's multi_logloss: 5.47866e-07	valid's multi_logloss: 0.125214
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1129]	train's multi_logloss: 5.46564e-07	valid's multi_logloss: 0.125204
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1130]	train's multi_logloss: 5.44246e-07	valid's multi_logloss: 0.125203
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1131]	train's multi_logloss: 5.42019e-07	valid's multi_logloss: 0.125204
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1132]	train's multi_logloss: 5.39728e-07	valid's multi_logloss: 0.125208
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1133]	train's multi_logloss: 5.37577e-07	valid's multi_logloss: 0.125213
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1134]	train's multi_logloss: 5.36031e-07	valid's multi_logloss: 0.1252
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1135]	train's multi_logloss: 5.33929e-07	valid's multi_logloss: 0.125209
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1136]	train's multi_logloss: 5.32324e-07	valid's multi_logloss: 0.1252
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1137]	train's multi_logloss: 5.30769e-07	valid's multi_logloss: 0.12521
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1138]	train's multi_logloss: 5.28641e-07	valid's multi_logloss: 0.1252
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1139]	train's multi_logloss: 5.273e-07	valid's multi_logloss: 0.125218
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1140]	train's multi_logloss: 5.25446e-07	valid's multi_logloss: 0.125225
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1141]	train's multi_logloss: 5.23505e-07	valid's multi_logloss: 0.125232
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1142]	train's multi_logloss: 5.21776e-07	valid's multi_logloss: 0.125219
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1143]	train's multi_logloss: 5.20261e-07	valid's multi_logloss: 0.125228
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1144]	train's multi_logloss: 5.18381e-07	valid's multi_logloss: 0.125225
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1145]	train's multi_logloss: 5.16893e-07	valid's multi_logloss: 0.125232
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1146]	train's multi_logloss: 5.15208e-07	valid's multi_logloss: 0.125225
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1147]	train's multi_logloss: 5.13956e-07	valid's multi_logloss: 0.125231
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1148]	train's multi_logloss: 5.12587e-07	valid's multi_logloss: 0.125251
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1149]	train's multi_logloss: 5.1123e-07	valid's multi_logloss: 0.125249
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1150]	train's multi_logloss: 5.09956e-07	valid's multi_logloss: 0.125269
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1151]	train's multi_logloss: 5.08257e-07	valid's multi_logloss: 0.125258
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1152]	train's multi_logloss: 5.06739e-07	valid's multi_logloss: 0.125246
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1153]	train's multi_logloss: 5.05573e-07	valid's multi_logloss: 0.125258
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1154]	train's multi_logloss: 5.0422e-07	valid's multi_logloss: 0.125246
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1155]	train's multi_logloss: 5.02983e-07	valid's multi_logloss: 0.125243
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1156]	train's multi_logloss: 5.01353e-07	valid's multi_logloss: 0.125267
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1157]	train's multi_logloss: 4.99878e-07	valid's multi_logloss: 0.125271
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1158]	train's multi_logloss: 4.98344e-07	valid's multi_logloss: 0.12528
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1159]	train's multi_logloss: 4.97034e-07	valid's multi_logloss: 0.125285
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1160]	train's multi_logloss: 4.9535e-07	valid's multi_logloss: 0.125297
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1161]	train's multi_logloss: 4.93838e-07	valid's multi_logloss: 0.125303
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1162]	train's multi_logloss: 4.9286e-07	valid's multi_logloss: 0.125316
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1163]	train's multi_logloss: 4.91859e-07	valid's multi_logloss: 0.12532
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1164]	train's multi_logloss: 4.90621e-07	valid's multi_logloss: 0.125336
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1165]	train's multi_logloss: 4.89647e-07	valid's multi_logloss: 0.125339
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1166]	train's multi_logloss: 4.88292e-07	valid's multi_logloss: 0.125354
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1167]	train's multi_logloss: 4.87255e-07	valid's multi_logloss: 0.125365
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1168]	train's multi_logloss: 4.86237e-07	valid's multi_logloss: 0.12538
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1169]	train's multi_logloss: 4.84955e-07	valid's multi_logloss: 0.125405
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1170]	train's multi_logloss: 4.8376e-07	valid's multi_logloss: 0.125409
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1171]	train's multi_logloss: 4.82615e-07	valid's multi_logloss: 0.12543
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1172]	train's multi_logloss: 4.81392e-07	valid's multi_logloss: 0.125443
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1173]	train's multi_logloss: 4.79993e-07	valid's multi_logloss: 0.125462
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1174]	train's multi_logloss: 4.78723e-07	valid's multi_logloss: 0.12546
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1175]	train's multi_logloss: 4.7792e-07	valid's multi_logloss: 0.125472
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1176]	train's multi_logloss: 4.76758e-07	valid's multi_logloss: 0.125479
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1177]	train's multi_logloss: 4.75608e-07	valid's multi_logloss: 0.125493
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1178]	train's multi_logloss: 4.74355e-07	valid's multi_logloss: 0.125515
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1179]	train's multi_logloss: 4.73084e-07	valid's multi_logloss: 0.125525
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1180]	train's multi_logloss: 4.72079e-07	valid's multi_logloss: 0.125526
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1181]	train's multi_logloss: 4.71465e-07	valid's multi_logloss: 0.125545
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1182]	train's multi_logloss: 4.70579e-07	valid's multi_logloss: 0.12555
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1183]	train's multi_logloss: 4.69772e-07	valid's multi_logloss: 0.125553
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1184]	train's multi_logloss: 4.68677e-07	valid's multi_logloss: 0.125558
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1185]	train's multi_logloss: 4.6757e-07	valid's multi_logloss: 0.125573
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1186]	train's multi_logloss: 4.66475e-07	valid's multi_logloss: 0.125594
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1187]	train's multi_logloss: 4.65366e-07	valid's multi_logloss: 0.12561
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1188]	train's multi_logloss: 4.64494e-07	valid's multi_logloss: 0.125624
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1189]	train's multi_logloss: 4.63505e-07	valid's multi_logloss: 0.125617
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1190]	train's multi_logloss: 4.62431e-07	valid's multi_logloss: 0.125615
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1191]	train's multi_logloss: 4.61329e-07	valid's multi_logloss: 0.125622
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1192]	train's multi_logloss: 4.60196e-07	valid's multi_logloss: 0.125631
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1193]	train's multi_logloss: 4.59234e-07	valid's multi_logloss: 0.125646
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1194]	train's multi_logloss: 4.58181e-07	valid's multi_logloss: 0.125649
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1195]	train's multi_logloss: 4.57179e-07	valid's multi_logloss: 0.125649
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1196]	train's multi_logloss: 4.56196e-07	valid's multi_logloss: 0.125656
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1197]	train's multi_logloss: 4.5519e-07	valid's multi_logloss: 0.125666
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1198]	train's multi_logloss: 4.54316e-07	valid's multi_logloss: 0.12566
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1199]	train's multi_logloss: 4.53121e-07	valid's multi_logloss: 0.125663
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1200]	train's multi_logloss: 4.52048e-07	valid's multi_logloss: 0.125689
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1201]	train's multi_logloss: 4.51092e-07	valid's multi_logloss: 0.125689
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1202]	train's multi_logloss: 4.50207e-07	valid's multi_logloss: 0.125683
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1203]	train's multi_logloss: 4.49312e-07	valid's multi_logloss: 0.125683
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1204]	train's multi_logloss: 4.48455e-07	valid's multi_logloss: 0.125701
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1205]	train's multi_logloss: 4.47309e-07	valid's multi_logloss: 0.125719
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1206]	train's multi_logloss: 4.46518e-07	valid's multi_logloss: 0.125716
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1207]	train's multi_logloss: 4.45219e-07	valid's multi_logloss: 0.125725
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1208]	train's multi_logloss: 4.44268e-07	valid's multi_logloss: 0.12573
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1209]	train's multi_logloss: 4.43138e-07	valid's multi_logloss: 0.125739
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1210]	train's multi_logloss: 4.4209e-07	valid's multi_logloss: 0.125748
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1211]	train's multi_logloss: 4.41208e-07	valid's multi_logloss: 0.125745
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1212]	train's multi_logloss: 4.4045e-07	valid's multi_logloss: 0.125742
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1213]	train's multi_logloss: 4.39619e-07	valid's multi_logloss: 0.125748
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1214]	train's multi_logloss: 4.38999e-07	valid's multi_logloss: 0.125741
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1215]	train's multi_logloss: 4.38063e-07	valid's multi_logloss: 0.125751
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1216]	train's multi_logloss: 4.37166e-07	valid's multi_logloss: 0.125759
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1217]	train's multi_logloss: 4.36186e-07	valid's multi_logloss: 0.125758
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1218]	train's multi_logloss: 4.35554e-07	valid's multi_logloss: 0.125766
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1219]	train's multi_logloss: 4.34707e-07	valid's multi_logloss: 0.125764
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1220]	train's multi_logloss: 4.3409e-07	valid's multi_logloss: 0.125771
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1221]	train's multi_logloss: 4.33213e-07	valid's multi_logloss: 0.125768
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1222]	train's multi_logloss: 4.32338e-07	valid's multi_logloss: 0.125774
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1223]	train's multi_logloss: 4.31498e-07	valid's multi_logloss: 0.125779
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1224]	train's multi_logloss: 4.30474e-07	valid's multi_logloss: 0.1258
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1225]	train's multi_logloss: 4.29657e-07	valid's multi_logloss: 0.125815
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1226]	train's multi_logloss: 4.28639e-07	valid's multi_logloss: 0.125842
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1227]	train's multi_logloss: 4.27692e-07	valid's multi_logloss: 0.12584
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1228]	train's multi_logloss: 4.26687e-07	valid's multi_logloss: 0.125851
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1229]	train's multi_logloss: 4.25752e-07	valid's multi_logloss: 0.125863
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1230]	train's multi_logloss: 4.24738e-07	valid's multi_logloss: 0.125858
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1231]	train's multi_logloss: 4.23969e-07	valid's multi_logloss: 0.125861
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1232]	train's multi_logloss: 4.23173e-07	valid's multi_logloss: 0.125874
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1233]	train's multi_logloss: 4.22323e-07	valid's multi_logloss: 0.125889
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1234]	train's multi_logloss: 4.21644e-07	valid's multi_logloss: 0.125881
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1235]	train's multi_logloss: 4.20934e-07	valid's multi_logloss: 0.125879
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1236]	train's multi_logloss: 4.20233e-07	valid's multi_logloss: 0.125893
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1237]	train's multi_logloss: 4.19597e-07	valid's multi_logloss: 0.125896
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1238]	train's multi_logloss: 4.18891e-07	valid's multi_logloss: 0.125912
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1239]	train's multi_logloss: 4.18122e-07	valid's multi_logloss: 0.125927
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1240]	train's multi_logloss: 4.1744e-07	valid's multi_logloss: 0.125928
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1241]	train's multi_logloss: 4.16778e-07	valid's multi_logloss: 0.125926
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1242]	train's multi_logloss: 4.1597e-07	valid's multi_logloss: 0.125933
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1243]	train's multi_logloss: 4.15109e-07	valid's multi_logloss: 0.125946
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1244]	train's multi_logloss: 4.14342e-07	valid's multi_logloss: 0.125959
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1245]	train's multi_logloss: 4.13565e-07	valid's multi_logloss: 0.125962
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1246]	train's multi_logloss: 4.12874e-07	valid's multi_logloss: 0.12597
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1247]	train's multi_logloss: 4.12239e-07	valid's multi_logloss: 0.125978
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1248]	train's multi_logloss: 4.11425e-07	valid's multi_logloss: 0.12599
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1249]	train's multi_logloss: 4.10768e-07	valid's multi_logloss: 0.125994
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1250]	train's multi_logloss: 4.10066e-07	valid's multi_logloss: 0.125993
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1251]	train's multi_logloss: 4.0932e-07	valid's multi_logloss: 0.125998
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1252]	train's multi_logloss: 4.08464e-07	valid's multi_logloss: 0.126008
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1253]	train's multi_logloss: 4.07763e-07	valid's multi_logloss: 0.126012
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1254]	train's multi_logloss: 4.07085e-07	valid's multi_logloss: 0.126013
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1255]	train's multi_logloss: 4.06637e-07	valid's multi_logloss: 0.126021
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1256]	train's multi_logloss: 4.05778e-07	valid's multi_logloss: 0.126031
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1257]	train's multi_logloss: 4.04957e-07	valid's multi_logloss: 0.126041
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1258]	train's multi_logloss: 4.04401e-07	valid's multi_logloss: 0.126035
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1259]	train's multi_logloss: 4.03913e-07	valid's multi_logloss: 0.126036
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1260]	train's multi_logloss: 4.0337e-07	valid's multi_logloss: 0.12603
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1261]	train's multi_logloss: 4.02872e-07	valid's multi_logloss: 0.126024
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1262]	train's multi_logloss: 4.0224e-07	valid's multi_logloss: 0.126034
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1263]	train's multi_logloss: 4.01508e-07	valid's multi_logloss: 0.126054
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1264]	train's multi_logloss: 4.00756e-07	valid's multi_logloss: 0.126057
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1265]	train's multi_logloss: 4.00087e-07	valid's multi_logloss: 0.126061
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1266]	train's multi_logloss: 3.99376e-07	valid's multi_logloss: 0.126076
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1267]	train's multi_logloss: 3.98869e-07	valid's multi_logloss: 0.126079
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1268]	train's multi_logloss: 3.98257e-07	valid's multi_logloss: 0.126093
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1269]	train's multi_logloss: 3.97653e-07	valid's multi_logloss: 0.126107
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1270]	train's multi_logloss: 3.97167e-07	valid's multi_logloss: 0.126108
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1271]	train's multi_logloss: 3.96457e-07	valid's multi_logloss: 0.126115
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1272]	train's multi_logloss: 3.95792e-07	valid's multi_logloss: 0.126133
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1273]	train's multi_logloss: 3.95307e-07	valid's multi_logloss: 0.126123
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1274]	train's multi_logloss: 3.94513e-07	valid's multi_logloss: 0.126146
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1275]	train's multi_logloss: 3.93729e-07	valid's multi_logloss: 0.126168
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1276]	train's multi_logloss: 3.93139e-07	valid's multi_logloss: 0.126163
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1277]	train's multi_logloss: 3.92665e-07	valid's multi_logloss: 0.126158
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1278]	train's multi_logloss: 3.9211e-07	valid's multi_logloss: 0.126173
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1279]	train's multi_logloss: 3.91423e-07	valid's multi_logloss: 0.126177
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1280]	train's multi_logloss: 3.90887e-07	valid's multi_logloss: 0.126193
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1281]	train's multi_logloss: 3.90345e-07	valid's multi_logloss: 0.126205
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1282]	train's multi_logloss: 3.89719e-07	valid's multi_logloss: 0.126219
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1283]	train's multi_logloss: 3.8905e-07	valid's multi_logloss: 0.126233
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1284]	train's multi_logloss: 3.88422e-07	valid's multi_logloss: 0.126251
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1285]	train's multi_logloss: 3.87908e-07	valid's multi_logloss: 0.126246
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1286]	train's multi_logloss: 3.87369e-07	valid's multi_logloss: 0.126252
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1287]	train's multi_logloss: 3.86613e-07	valid's multi_logloss: 0.126269
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1288]	train's multi_logloss: 3.86052e-07	valid's multi_logloss: 0.126275
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1289]	train's multi_logloss: 3.85469e-07	valid's multi_logloss: 0.126286
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1290]	train's multi_logloss: 3.84825e-07	valid's multi_logloss: 0.126295
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1291]	train's multi_logloss: 3.84342e-07	valid's multi_logloss: 0.126304
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1292]	train's multi_logloss: 3.83734e-07	valid's multi_logloss: 0.126315
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1293]	train's multi_logloss: 3.83206e-07	valid's multi_logloss: 0.126318
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1294]	train's multi_logloss: 3.82691e-07	valid's multi_logloss: 0.12633
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1295]	train's multi_logloss: 3.82174e-07	valid's multi_logloss: 0.126335
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1296]	train's multi_logloss: 3.81538e-07	valid's multi_logloss: 0.126356
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1297]	train's multi_logloss: 3.81122e-07	valid's multi_logloss: 0.126356
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1298]	train's multi_logloss: 3.80604e-07	valid's multi_logloss: 0.126363
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1299]	train's multi_logloss: 3.80105e-07	valid's multi_logloss: 0.12637
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1300]	train's multi_logloss: 3.79685e-07	valid's multi_logloss: 0.126387
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1301]	train's multi_logloss: 3.79089e-07	valid's multi_logloss: 0.126393
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1302]	train's multi_logloss: 3.78646e-07	valid's multi_logloss: 0.126392
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1303]	train's multi_logloss: 3.78126e-07	valid's multi_logloss: 0.126395
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1304]	train's multi_logloss: 3.77531e-07	valid's multi_logloss: 0.126402
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1305]	train's multi_logloss: 3.77149e-07	valid's multi_logloss: 0.126417
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1306]	train's multi_logloss: 3.76804e-07	valid's multi_logloss: 0.126424
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1307]	train's multi_logloss: 3.7635e-07	valid's multi_logloss: 0.126437
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1308]	train's multi_logloss: 3.75792e-07	valid's multi_logloss: 0.126445
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1309]	train's multi_logloss: 3.75311e-07	valid's multi_logloss: 0.12645
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1310]	train's multi_logloss: 3.74761e-07	valid's multi_logloss: 0.126463
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1311]	train's multi_logloss: 3.74389e-07	valid's multi_logloss: 0.126454
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1312]	train's multi_logloss: 3.73846e-07	valid's multi_logloss: 0.12647
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1313]	train's multi_logloss: 3.73502e-07	valid's multi_logloss: 0.126465
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1314]	train's multi_logloss: 3.72869e-07	valid's multi_logloss: 0.126481
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1315]	train's multi_logloss: 3.72417e-07	valid's multi_logloss: 0.126494
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1316]	train's multi_logloss: 3.72078e-07	valid's multi_logloss: 0.12649
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1317]	train's multi_logloss: 3.71548e-07	valid's multi_logloss: 0.126507
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1318]	train's multi_logloss: 3.71197e-07	valid's multi_logloss: 0.126505
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1319]	train's multi_logloss: 3.7066e-07	valid's multi_logloss: 0.126507
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1320]	train's multi_logloss: 3.70291e-07	valid's multi_logloss: 0.126509
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1321]	train's multi_logloss: 3.69858e-07	valid's multi_logloss: 0.126523
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1322]	train's multi_logloss: 3.69535e-07	valid's multi_logloss: 0.126519
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1323]	train's multi_logloss: 3.6904e-07	valid's multi_logloss: 0.126528
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1324]	train's multi_logloss: 3.68622e-07	valid's multi_logloss: 0.126531
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1325]	train's multi_logloss: 3.68289e-07	valid's multi_logloss: 0.12653
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1326]	train's multi_logloss: 3.67878e-07	valid's multi_logloss: 0.126535
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1327]	train's multi_logloss: 3.67399e-07	valid's multi_logloss: 0.126549
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1328]	train's multi_logloss: 3.67116e-07	valid's multi_logloss: 0.126554
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1329]	train's multi_logloss: 3.66635e-07	valid's multi_logloss: 0.126568
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1330]	train's multi_logloss: 3.66222e-07	valid's multi_logloss: 0.126588
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1331]	train's multi_logloss: 3.65741e-07	valid's multi_logloss: 0.126587
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1332]	train's multi_logloss: 3.65263e-07	valid's multi_logloss: 0.126591
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1333]	train's multi_logloss: 3.64922e-07	valid's multi_logloss: 0.126586
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1334]	train's multi_logloss: 3.64535e-07	valid's multi_logloss: 0.126596
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1335]	train's multi_logloss: 3.64136e-07	valid's multi_logloss: 0.126602
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1336]	train's multi_logloss: 3.63847e-07	valid's multi_logloss: 0.126606
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1337]	train's multi_logloss: 3.63379e-07	valid's multi_logloss: 0.126603
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1338]	train's multi_logloss: 3.63047e-07	valid's multi_logloss: 0.126601
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1339]	train's multi_logloss: 3.62814e-07	valid's multi_logloss: 0.126604
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1340]	train's multi_logloss: 3.62441e-07	valid's multi_logloss: 0.126611
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1341]	train's multi_logloss: 3.62068e-07	valid's multi_logloss: 0.126607
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1342]	train's multi_logloss: 3.61742e-07	valid's multi_logloss: 0.12661
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1343]	train's multi_logloss: 3.61419e-07	valid's multi_logloss: 0.126613
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1344]	train's multi_logloss: 3.61081e-07	valid's multi_logloss: 0.126619
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1345]	train's multi_logloss: 3.60723e-07	valid's multi_logloss: 0.126616
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1346]	train's multi_logloss: 3.60403e-07	valid's multi_logloss: 0.126619
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1347]	train's multi_logloss: 3.59966e-07	valid's multi_logloss: 0.126615
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1348]	train's multi_logloss: 3.59592e-07	valid's multi_logloss: 0.126618
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1349]	train's multi_logloss: 3.59194e-07	valid's multi_logloss: 0.126633
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1350]	train's multi_logloss: 3.58798e-07	valid's multi_logloss: 0.126636
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1351]	train's multi_logloss: 3.58455e-07	valid's multi_logloss: 0.126645
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1352]	train's multi_logloss: 3.58148e-07	valid's multi_logloss: 0.126643
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1353]	train's multi_logloss: 3.5781e-07	valid's multi_logloss: 0.126651
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1354]	train's multi_logloss: 3.57452e-07	valid's multi_logloss: 0.126657
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1355]	train's multi_logloss: 3.57098e-07	valid's multi_logloss: 0.126658
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1356]	train's multi_logloss: 3.56832e-07	valid's multi_logloss: 0.126663
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1357]	train's multi_logloss: 3.5643e-07	valid's multi_logloss: 0.126678
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1358]	train's multi_logloss: 3.56137e-07	valid's multi_logloss: 0.12668
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1359]	train's multi_logloss: 3.55603e-07	valid's multi_logloss: 0.126678
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1360]	train's multi_logloss: 3.55254e-07	valid's multi_logloss: 0.126675
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1361]	train's multi_logloss: 3.54832e-07	valid's multi_logloss: 0.126682
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1362]	train's multi_logloss: 3.54519e-07	valid's multi_logloss: 0.126688
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1363]	train's multi_logloss: 3.54085e-07	valid's multi_logloss: 0.126683
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1364]	train's multi_logloss: 3.53764e-07	valid's multi_logloss: 0.126689
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1365]	train's multi_logloss: 3.53247e-07	valid's multi_logloss: 0.126686
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1366]	train's multi_logloss: 3.529e-07	valid's multi_logloss: 0.1267
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1367]	train's multi_logloss: 3.52597e-07	valid's multi_logloss: 0.126706
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1368]	train's multi_logloss: 3.52248e-07	valid's multi_logloss: 0.126711
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1369]	train's multi_logloss: 3.51823e-07	valid's multi_logloss: 0.126708
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1370]	train's multi_logloss: 3.51479e-07	valid's multi_logloss: 0.126713
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1371]	train's multi_logloss: 3.51059e-07	valid's multi_logloss: 0.126714
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1372]	train's multi_logloss: 3.50729e-07	valid's multi_logloss: 0.126718
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1373]	train's multi_logloss: 3.50412e-07	valid's multi_logloss: 0.12672
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1374]	train's multi_logloss: 3.5011e-07	valid's multi_logloss: 0.126731
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1375]	train's multi_logloss: 3.49785e-07	valid's multi_logloss: 0.126731
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1376]	train's multi_logloss: 3.49447e-07	valid's multi_logloss: 0.126727
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1377]	train's multi_logloss: 3.49132e-07	valid's multi_logloss: 0.126732
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1378]	train's multi_logloss: 3.48811e-07	valid's multi_logloss: 0.126728
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1379]	train's multi_logloss: 3.48506e-07	valid's multi_logloss: 0.126736
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1380]	train's multi_logloss: 3.48183e-07	valid's multi_logloss: 0.126736
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1381]	train's multi_logloss: 3.47837e-07	valid's multi_logloss: 0.126738
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1382]	train's multi_logloss: 3.4748e-07	valid's multi_logloss: 0.126748
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1383]	train's multi_logloss: 3.47173e-07	valid's multi_logloss: 0.126755
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1384]	train's multi_logloss: 3.46887e-07	valid's multi_logloss: 0.126758
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1385]	train's multi_logloss: 3.46595e-07	valid's multi_logloss: 0.126762
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1386]	train's multi_logloss: 3.46296e-07	valid's multi_logloss: 0.126764
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1387]	train's multi_logloss: 3.46021e-07	valid's multi_logloss: 0.126759
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1388]	train's multi_logloss: 3.45707e-07	valid's multi_logloss: 0.126756
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1389]	train's multi_logloss: 3.45489e-07	valid's multi_logloss: 0.126755
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1390]	train's multi_logloss: 3.45207e-07	valid's multi_logloss: 0.126762
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1391]	train's multi_logloss: 3.44918e-07	valid's multi_logloss: 0.126769
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1392]	train's multi_logloss: 3.44675e-07	valid's multi_logloss: 0.12678
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1393]	train's multi_logloss: 3.4446e-07	valid's multi_logloss: 0.12678
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1394]	train's multi_logloss: 3.44243e-07	valid's multi_logloss: 0.126783
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1395]	train's multi_logloss: 3.43928e-07	valid's multi_logloss: 0.126786
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1396]	train's multi_logloss: 3.43638e-07	valid's multi_logloss: 0.126786
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1397]	train's multi_logloss: 3.43357e-07	valid's multi_logloss: 0.126793
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1398]	train's multi_logloss: 3.43142e-07	valid's multi_logloss: 0.126798
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1399]	train's multi_logloss: 3.42868e-07	valid's multi_logloss: 0.1268
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1400]	train's multi_logloss: 3.42592e-07	valid's multi_logloss: 0.1268
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1401]	train's multi_logloss: 3.42267e-07	valid's multi_logloss: 0.126801
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1402]	train's multi_logloss: 3.41962e-07	valid's multi_logloss: 0.126805
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1403]	train's multi_logloss: 3.41663e-07	valid's multi_logloss: 0.126812
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1404]	train's multi_logloss: 3.41454e-07	valid's multi_logloss: 0.12681
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1405]	train's multi_logloss: 3.41155e-07	valid's multi_logloss: 0.126819
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1406]	train's multi_logloss: 3.40918e-07	valid's multi_logloss: 0.126828
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1407]	train's multi_logloss: 3.40579e-07	valid's multi_logloss: 0.126838
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1408]	train's multi_logloss: 3.40269e-07	valid's multi_logloss: 0.126846
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1409]	train's multi_logloss: 3.40066e-07	valid's multi_logloss: 0.126847
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1410]	train's multi_logloss: 3.39786e-07	valid's multi_logloss: 0.126856
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1411]	train's multi_logloss: 3.39525e-07	valid's multi_logloss: 0.12686
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1412]	train's multi_logloss: 3.39201e-07	valid's multi_logloss: 0.126873
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1413]	train's multi_logloss: 3.38942e-07	valid's multi_logloss: 0.126878
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1414]	train's multi_logloss: 3.3868e-07	valid's multi_logloss: 0.126885
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1415]	train's multi_logloss: 3.38361e-07	valid's multi_logloss: 0.126895
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1416]	train's multi_logloss: 3.38029e-07	valid's multi_logloss: 0.126909
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1417]	train's multi_logloss: 3.37719e-07	valid's multi_logloss: 0.126913
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1418]	train's multi_logloss: 3.37402e-07	valid's multi_logloss: 0.126915
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1419]	train's multi_logloss: 3.37087e-07	valid's multi_logloss: 0.126928
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1420]	train's multi_logloss: 3.36795e-07	valid's multi_logloss: 0.126923
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1421]	train's multi_logloss: 3.36467e-07	valid's multi_logloss: 0.126933
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1422]	train's multi_logloss: 3.362e-07	valid's multi_logloss: 0.12693
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1423]	train's multi_logloss: 3.35936e-07	valid's multi_logloss: 0.126932
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1424]	train's multi_logloss: 3.35656e-07	valid's multi_logloss: 0.126932
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1425]	train's multi_logloss: 3.35396e-07	valid's multi_logloss: 0.126933
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1426]	train's multi_logloss: 3.35143e-07	valid's multi_logloss: 0.126934
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1427]	train's multi_logloss: 3.34899e-07	valid's multi_logloss: 0.126942
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1428]	train's multi_logloss: 3.34684e-07	valid's multi_logloss: 0.126946
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1429]	train's multi_logloss: 3.34455e-07	valid's multi_logloss: 0.126949
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1430]	train's multi_logloss: 3.34223e-07	valid's multi_logloss: 0.126952
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1431]	train's multi_logloss: 3.34034e-07	valid's multi_logloss: 0.126957
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1432]	train's multi_logloss: 3.33817e-07	valid's multi_logloss: 0.126962
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1433]	train's multi_logloss: 3.33559e-07	valid's multi_logloss: 0.126963
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1434]	train's multi_logloss: 3.33325e-07	valid's multi_logloss: 0.126969
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1435]	train's multi_logloss: 3.33096e-07	valid's multi_logloss: 0.126971
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1436]	train's multi_logloss: 3.32852e-07	valid's multi_logloss: 0.12698
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1437]	train's multi_logloss: 3.32629e-07	valid's multi_logloss: 0.126984
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1438]	train's multi_logloss: 3.32369e-07	valid's multi_logloss: 0.126986
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1439]	train's multi_logloss: 3.32171e-07	valid's multi_logloss: 0.126993
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1440]	train's multi_logloss: 3.31878e-07	valid's multi_logloss: 0.126997
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1441]	train's multi_logloss: 3.3159e-07	valid's multi_logloss: 0.127008
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1442]	train's multi_logloss: 3.31278e-07	valid's multi_logloss: 0.127008
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1443]	train's multi_logloss: 3.31011e-07	valid's multi_logloss: 0.127006
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1444]	train's multi_logloss: 3.30758e-07	valid's multi_logloss: 0.127001
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1445]	train's multi_logloss: 3.30475e-07	valid's multi_logloss: 0.127013
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1446]	train's multi_logloss: 3.30193e-07	valid's multi_logloss: 0.127022
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1447]	train's multi_logloss: 3.29931e-07	valid's multi_logloss: 0.127015
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1448]	train's multi_logloss: 3.29754e-07	valid's multi_logloss: 0.12702
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1449]	train's multi_logloss: 3.29487e-07	valid's multi_logloss: 0.12702
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1450]	train's multi_logloss: 3.29236e-07	valid's multi_logloss: 0.12702
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1451]	train's multi_logloss: 3.2899e-07	valid's multi_logloss: 0.127022
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1452]	train's multi_logloss: 3.28739e-07	valid's multi_logloss: 0.12703
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1453]	train's multi_logloss: 3.28496e-07	valid's multi_logloss: 0.127033
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1454]	train's multi_logloss: 3.2825e-07	valid's multi_logloss: 0.127032
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1455]	train's multi_logloss: 3.28057e-07	valid's multi_logloss: 0.127041
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1456]	train's multi_logloss: 3.27762e-07	valid's multi_logloss: 0.12705
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1457]	train's multi_logloss: 3.27577e-07	valid's multi_logloss: 0.127059
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1458]	train's multi_logloss: 3.27375e-07	valid's multi_logloss: 0.127068
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1459]	train's multi_logloss: 3.27187e-07	valid's multi_logloss: 0.127076
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1460]	train's multi_logloss: 3.26908e-07	valid's multi_logloss: 0.127085
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1461]	train's multi_logloss: 3.26636e-07	valid's multi_logloss: 0.127096
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1462]	train's multi_logloss: 3.2641e-07	valid's multi_logloss: 0.127089
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1463]	train's multi_logloss: 3.2614e-07	valid's multi_logloss: 0.127097
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1464]	train's multi_logloss: 3.25917e-07	valid's multi_logloss: 0.12709
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1465]	train's multi_logloss: 3.2565e-07	valid's multi_logloss: 0.127101
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1466]	train's multi_logloss: 3.25434e-07	valid's multi_logloss: 0.127095
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1467]	train's multi_logloss: 3.25191e-07	valid's multi_logloss: 0.127095
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1468]	train's multi_logloss: 3.24953e-07	valid's multi_logloss: 0.127091
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1469]	train's multi_logloss: 3.24786e-07	valid's multi_logloss: 0.127096
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1470]	train's multi_logloss: 3.24577e-07	valid's multi_logloss: 0.127098
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1471]	train's multi_logloss: 3.24331e-07	valid's multi_logloss: 0.127103
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1472]	train's multi_logloss: 3.24141e-07	valid's multi_logloss: 0.127105
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1473]	train's multi_logloss: 3.23915e-07	valid's multi_logloss: 0.127101
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1474]	train's multi_logloss: 3.23748e-07	valid's multi_logloss: 0.127101
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1475]	train's multi_logloss: 3.23546e-07	valid's multi_logloss: 0.127111
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1476]	train's multi_logloss: 3.23309e-07	valid's multi_logloss: 0.127116
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1477]	train's multi_logloss: 3.23118e-07	valid's multi_logloss: 0.127124
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1478]	train's multi_logloss: 3.22897e-07	valid's multi_logloss: 0.127123
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1479]	train's multi_logloss: 3.22685e-07	valid's multi_logloss: 0.127119
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1480]	train's multi_logloss: 3.22509e-07	valid's multi_logloss: 0.127134
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1481]	train's multi_logloss: 3.22335e-07	valid's multi_logloss: 0.127132
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1482]	train's multi_logloss: 3.22137e-07	valid's multi_logloss: 0.12714
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1483]	train's multi_logloss: 3.21898e-07	valid's multi_logloss: 0.127139
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1484]	train's multi_logloss: 3.21703e-07	valid's multi_logloss: 0.12715
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1485]	train's multi_logloss: 3.21529e-07	valid's multi_logloss: 0.127156
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1486]	train's multi_logloss: 3.21304e-07	valid's multi_logloss: 0.127155
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1487]	train's multi_logloss: 3.21111e-07	valid's multi_logloss: 0.127163
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1488]	train's multi_logloss: 3.20918e-07	valid's multi_logloss: 0.127169
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1489]	train's multi_logloss: 3.20676e-07	valid's multi_logloss: 0.127177
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1490]	train's multi_logloss: 3.20481e-07	valid's multi_logloss: 0.127179
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1491]	train's multi_logloss: 3.20291e-07	valid's multi_logloss: 0.127182
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1492]	train's multi_logloss: 3.20114e-07	valid's multi_logloss: 0.127189
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1493]	train's multi_logloss: 3.19904e-07	valid's multi_logloss: 0.127197
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1494]	train's multi_logloss: 3.19719e-07	valid's multi_logloss: 0.127208
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1495]	train's multi_logloss: 3.1954e-07	valid's multi_logloss: 0.127207
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1496]	train's multi_logloss: 3.19334e-07	valid's multi_logloss: 0.127202
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1497]	train's multi_logloss: 3.19129e-07	valid's multi_logloss: 0.12721
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1498]	train's multi_logloss: 3.18868e-07	valid's multi_logloss: 0.127221
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1499]	train's multi_logloss: 3.18682e-07	valid's multi_logloss: 0.12722
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1500]	train's multi_logloss: 3.18494e-07	valid's multi_logloss: 0.127227
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1501]	train's multi_logloss: 3.18303e-07	valid's multi_logloss: 0.127229
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1502]	train's multi_logloss: 3.18031e-07	valid's multi_logloss: 0.127242
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1503]	train's multi_logloss: 3.17785e-07	valid's multi_logloss: 0.127255
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1504]	train's multi_logloss: 3.17558e-07	valid's multi_logloss: 0.127256
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1505]	train's multi_logloss: 3.17374e-07	valid's multi_logloss: 0.127254
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1506]	train's multi_logloss: 3.17192e-07	valid's multi_logloss: 0.127256
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1507]	train's multi_logloss: 3.17019e-07	valid's multi_logloss: 0.127259
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1508]	train's multi_logloss: 3.16815e-07	valid's multi_logloss: 0.12725
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1509]	train's multi_logloss: 3.16636e-07	valid's multi_logloss: 0.127257
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1510]	train's multi_logloss: 3.16435e-07	valid's multi_logloss: 0.127251
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1511]	train's multi_logloss: 3.16235e-07	valid's multi_logloss: 0.127259
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1512]	train's multi_logloss: 3.16036e-07	valid's multi_logloss: 0.127258
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1513]	train's multi_logloss: 3.15795e-07	valid's multi_logloss: 0.127269
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1514]	train's multi_logloss: 3.15587e-07	valid's multi_logloss: 0.127278
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1515]	train's multi_logloss: 3.15428e-07	valid's multi_logloss: 0.127293
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1516]	train's multi_logloss: 3.15251e-07	valid's multi_logloss: 0.127303
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1517]	train's multi_logloss: 3.15061e-07	valid's multi_logloss: 0.127305
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1518]	train's multi_logloss: 3.14888e-07	valid's multi_logloss: 0.127315
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1519]	train's multi_logloss: 3.14719e-07	valid's multi_logloss: 0.127326
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1520]	train's multi_logloss: 3.14519e-07	valid's multi_logloss: 0.127327
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1521]	train's multi_logloss: 3.14292e-07	valid's multi_logloss: 0.127325
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1522]	train's multi_logloss: 3.14099e-07	valid's multi_logloss: 0.127324
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1523]	train's multi_logloss: 3.1389e-07	valid's multi_logloss: 0.127315
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1524]	train's multi_logloss: 3.13691e-07	valid's multi_logloss: 0.127305
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1525]	train's multi_logloss: 3.13491e-07	valid's multi_logloss: 0.1273
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1526]	train's multi_logloss: 3.13309e-07	valid's multi_logloss: 0.127299
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1527]	train's multi_logloss: 3.13127e-07	valid's multi_logloss: 0.127298
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1528]	train's multi_logloss: 3.12958e-07	valid's multi_logloss: 0.127305
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1529]	train's multi_logloss: 3.12774e-07	valid's multi_logloss: 0.127302
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1530]	train's multi_logloss: 3.12572e-07	valid's multi_logloss: 0.127301
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1531]	train's multi_logloss: 3.12363e-07	valid's multi_logloss: 0.127297
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1532]	train's multi_logloss: 3.12193e-07	valid's multi_logloss: 0.127292
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1533]	train's multi_logloss: 3.11986e-07	valid's multi_logloss: 0.127285
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1534]	train's multi_logloss: 3.1179e-07	valid's multi_logloss: 0.127288
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1535]	train's multi_logloss: 3.11598e-07	valid's multi_logloss: 0.127283
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1536]	train's multi_logloss: 3.1142e-07	valid's multi_logloss: 0.127282
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1537]	train's multi_logloss: 3.1123e-07	valid's multi_logloss: 0.127278
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1538]	train's multi_logloss: 3.10996e-07	valid's multi_logloss: 0.127285
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1539]	train's multi_logloss: 3.10803e-07	valid's multi_logloss: 0.127276
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1540]	train's multi_logloss: 3.10603e-07	valid's multi_logloss: 0.12728
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1541]	train's multi_logloss: 3.1041e-07	valid's multi_logloss: 0.127283
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1542]	train's multi_logloss: 3.1021e-07	valid's multi_logloss: 0.127278
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1543]	train's multi_logloss: 3.09996e-07	valid's multi_logloss: 0.127282
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1544]	train's multi_logloss: 3.09807e-07	valid's multi_logloss: 0.127282
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1545]	train's multi_logloss: 3.09618e-07	valid's multi_logloss: 0.127277
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1546]	train's multi_logloss: 3.09417e-07	valid's multi_logloss: 0.127281
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1547]	train's multi_logloss: 3.09255e-07	valid's multi_logloss: 0.127276
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1548]	train's multi_logloss: 3.09102e-07	valid's multi_logloss: 0.127285
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1549]	train's multi_logloss: 3.08908e-07	valid's multi_logloss: 0.12729
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1550]	train's multi_logloss: 3.08743e-07	valid's multi_logloss: 0.127295
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1551]	train's multi_logloss: 3.08561e-07	valid's multi_logloss: 0.127289
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1552]	train's multi_logloss: 3.08416e-07	valid's multi_logloss: 0.127296
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1553]	train's multi_logloss: 3.08265e-07	valid's multi_logloss: 0.127305
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1554]	train's multi_logloss: 3.08087e-07	valid's multi_logloss: 0.127308
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1555]	train's multi_logloss: 3.07924e-07	valid's multi_logloss: 0.127316
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1556]	train's multi_logloss: 3.07742e-07	valid's multi_logloss: 0.127309
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1557]	train's multi_logloss: 3.07566e-07	valid's multi_logloss: 0.127311
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1558]	train's multi_logloss: 3.07415e-07	valid's multi_logloss: 0.127317
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1559]	train's multi_logloss: 3.07226e-07	valid's multi_logloss: 0.127322
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1560]	train's multi_logloss: 3.07053e-07	valid's multi_logloss: 0.127326
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1561]	train's multi_logloss: 3.06909e-07	valid's multi_logloss: 0.127329
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1562]	train's multi_logloss: 3.06696e-07	valid's multi_logloss: 0.127327
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1563]	train's multi_logloss: 3.06515e-07	valid's multi_logloss: 0.127323
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1564]	train's multi_logloss: 3.06338e-07	valid's multi_logloss: 0.127324
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1565]	train's multi_logloss: 3.06196e-07	valid's multi_logloss: 0.127336
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1566]	train's multi_logloss: 3.05973e-07	valid's multi_logloss: 0.127331
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1567]	train's multi_logloss: 3.05809e-07	valid's multi_logloss: 0.127338
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1568]	train's multi_logloss: 3.05617e-07	valid's multi_logloss: 0.12735
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1569]	train's multi_logloss: 3.05469e-07	valid's multi_logloss: 0.127348
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1570]	train's multi_logloss: 3.05293e-07	valid's multi_logloss: 0.127343
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1571]	train's multi_logloss: 3.05144e-07	valid's multi_logloss: 0.127352
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1572]	train's multi_logloss: 3.04972e-07	valid's multi_logloss: 0.127347
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1573]	train's multi_logloss: 3.04795e-07	valid's multi_logloss: 0.127353
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1574]	train's multi_logloss: 3.0462e-07	valid's multi_logloss: 0.12735
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1575]	train's multi_logloss: 3.04462e-07	valid's multi_logloss: 0.12736
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1576]	train's multi_logloss: 3.0429e-07	valid's multi_logloss: 0.127352
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1577]	train's multi_logloss: 3.04108e-07	valid's multi_logloss: 0.127356
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1578]	train's multi_logloss: 3.03952e-07	valid's multi_logloss: 0.127363
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1579]	train's multi_logloss: 3.03778e-07	valid's multi_logloss: 0.127359
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1580]	train's multi_logloss: 3.03621e-07	valid's multi_logloss: 0.127365
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1581]	train's multi_logloss: 3.0346e-07	valid's multi_logloss: 0.127364
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1582]	train's multi_logloss: 3.03276e-07	valid's multi_logloss: 0.127362
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1583]	train's multi_logloss: 3.0314e-07	valid's multi_logloss: 0.127365
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1584]	train's multi_logloss: 3.02992e-07	valid's multi_logloss: 0.127366
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1585]	train's multi_logloss: 3.02819e-07	valid's multi_logloss: 0.127373
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1586]	train's multi_logloss: 3.02656e-07	valid's multi_logloss: 0.127378
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1587]	train's multi_logloss: 3.02453e-07	valid's multi_logloss: 0.127369
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1588]	train's multi_logloss: 3.02282e-07	valid's multi_logloss: 0.127379
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1589]	train's multi_logloss: 3.02005e-07	valid's multi_logloss: 0.12739
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1590]	train's multi_logloss: 3.01848e-07	valid's multi_logloss: 0.127388
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1591]	train's multi_logloss: 3.01694e-07	valid's multi_logloss: 0.127391
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1592]	train's multi_logloss: 3.014e-07	valid's multi_logloss: 0.127406
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1593]	train's multi_logloss: 3.01257e-07	valid's multi_logloss: 0.127408
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1594]	train's multi_logloss: 3.01084e-07	valid's multi_logloss: 0.127409
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1595]	train's multi_logloss: 3.00819e-07	valid's multi_logloss: 0.12742
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1596]	train's multi_logloss: 3.00652e-07	valid's multi_logloss: 0.127416
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1597]	train's multi_logloss: 3.00361e-07	valid's multi_logloss: 0.127428
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1598]	train's multi_logloss: 3.00207e-07	valid's multi_logloss: 0.127427
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1599]	train's multi_logloss: 3.00034e-07	valid's multi_logloss: 0.127431
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1600]	train's multi_logloss: 2.99774e-07	valid's multi_logloss: 0.127435
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1601]	train's multi_logloss: 2.9953e-07	valid's multi_logloss: 0.127448
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1602]	train's multi_logloss: 2.99324e-07	valid's multi_logloss: 0.12744
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1603]	train's multi_logloss: 2.99137e-07	valid's multi_logloss: 0.12744
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1604]	train's multi_logloss: 2.98993e-07	valid's multi_logloss: 0.12744
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1605]	train's multi_logloss: 2.98858e-07	valid's multi_logloss: 0.127442
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1606]	train's multi_logloss: 2.98614e-07	valid's multi_logloss: 0.127441
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1607]	train's multi_logloss: 2.98469e-07	valid's multi_logloss: 0.127445
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1608]	train's multi_logloss: 2.98309e-07	valid's multi_logloss: 0.12745
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1609]	train's multi_logloss: 2.98047e-07	valid's multi_logloss: 0.127456
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1610]	train's multi_logloss: 2.97904e-07	valid's multi_logloss: 0.127453
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1611]	train's multi_logloss: 2.97762e-07	valid's multi_logloss: 0.127461
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1612]	train's multi_logloss: 2.97587e-07	valid's multi_logloss: 0.127458
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1613]	train's multi_logloss: 2.97416e-07	valid's multi_logloss: 0.127464
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1614]	train's multi_logloss: 2.97235e-07	valid's multi_logloss: 0.127463
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1615]	train's multi_logloss: 2.96987e-07	valid's multi_logloss: 0.127475
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1616]	train's multi_logloss: 2.96751e-07	valid's multi_logloss: 0.127488
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1617]	train's multi_logloss: 2.96611e-07	valid's multi_logloss: 0.127494
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1618]	train's multi_logloss: 2.9643e-07	valid's multi_logloss: 0.127492
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1619]	train's multi_logloss: 2.96261e-07	valid's multi_logloss: 0.127492
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1620]	train's multi_logloss: 2.96094e-07	valid's multi_logloss: 0.127488
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1621]	train's multi_logloss: 2.95877e-07	valid's multi_logloss: 0.1275
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1622]	train's multi_logloss: 2.95717e-07	valid's multi_logloss: 0.1275
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1623]	train's multi_logloss: 2.95566e-07	valid's multi_logloss: 0.127504
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1624]	train's multi_logloss: 2.95407e-07	valid's multi_logloss: 0.127504
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1625]	train's multi_logloss: 2.95271e-07	valid's multi_logloss: 0.127503
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1626]	train's multi_logloss: 2.95141e-07	valid's multi_logloss: 0.127503
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1627]	train's multi_logloss: 2.94975e-07	valid's multi_logloss: 0.127507
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1628]	train's multi_logloss: 2.94808e-07	valid's multi_logloss: 0.127507
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1629]	train's multi_logloss: 2.9464e-07	valid's multi_logloss: 0.127506
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1630]	train's multi_logloss: 2.94474e-07	valid's multi_logloss: 0.127506
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1631]	train's multi_logloss: 2.94332e-07	valid's multi_logloss: 0.127504
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1632]	train's multi_logloss: 2.94167e-07	valid's multi_logloss: 0.127504
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1633]	train's multi_logloss: 2.9397e-07	valid's multi_logloss: 0.127504
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1634]	train's multi_logloss: 2.93728e-07	valid's multi_logloss: 0.127514
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1635]	train's multi_logloss: 2.93569e-07	valid's multi_logloss: 0.127518
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1636]	train's multi_logloss: 2.93309e-07	valid's multi_logloss: 0.127528
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1637]	train's multi_logloss: 2.93154e-07	valid's multi_logloss: 0.127529
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1638]	train's multi_logloss: 2.92917e-07	valid's multi_logloss: 0.127538
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1639]	train's multi_logloss: 2.92758e-07	valid's multi_logloss: 0.127538
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1640]	train's multi_logloss: 2.92588e-07	valid's multi_logloss: 0.127532
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1641]	train's multi_logloss: 2.92443e-07	valid's multi_logloss: 0.127531
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1642]	train's multi_logloss: 2.92326e-07	valid's multi_logloss: 0.127534
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1643]	train's multi_logloss: 2.92174e-07	valid's multi_logloss: 0.127538
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1644]	train's multi_logloss: 2.91966e-07	valid's multi_logloss: 0.127555
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1645]	train's multi_logloss: 2.91859e-07	valid's multi_logloss: 0.127559
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1646]	train's multi_logloss: 2.91718e-07	valid's multi_logloss: 0.127568
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1647]	train's multi_logloss: 2.91569e-07	valid's multi_logloss: 0.127567
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1648]	train's multi_logloss: 2.91392e-07	valid's multi_logloss: 0.127575
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1649]	train's multi_logloss: 2.91256e-07	valid's multi_logloss: 0.12757
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1650]	train's multi_logloss: 2.91091e-07	valid's multi_logloss: 0.127579
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1651]	train's multi_logloss: 2.90946e-07	valid's multi_logloss: 0.127573
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1652]	train's multi_logloss: 2.90787e-07	valid's multi_logloss: 0.127573
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1653]	train's multi_logloss: 2.90649e-07	valid's multi_logloss: 0.127572
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1654]	train's multi_logloss: 2.90492e-07	valid's multi_logloss: 0.127572
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1655]	train's multi_logloss: 2.90266e-07	valid's multi_logloss: 0.127583
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1656]	train's multi_logloss: 2.9012e-07	valid's multi_logloss: 0.12758
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1657]	train's multi_logloss: 2.89957e-07	valid's multi_logloss: 0.127586
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1658]	train's multi_logloss: 2.89798e-07	valid's multi_logloss: 0.127585
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1659]	train's multi_logloss: 2.89644e-07	valid's multi_logloss: 0.127585
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1660]	train's multi_logloss: 2.89413e-07	valid's multi_logloss: 0.12759
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1661]	train's multi_logloss: 2.89274e-07	valid's multi_logloss: 0.127591
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1662]	train's multi_logloss: 2.89146e-07	valid's multi_logloss: 0.1276
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1663]	train's multi_logloss: 2.88905e-07	valid's multi_logloss: 0.127613
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1664]	train's multi_logloss: 2.88769e-07	valid's multi_logloss: 0.127608
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1665]	train's multi_logloss: 2.88639e-07	valid's multi_logloss: 0.12761
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1666]	train's multi_logloss: 2.88525e-07	valid's multi_logloss: 0.127614
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1667]	train's multi_logloss: 2.88364e-07	valid's multi_logloss: 0.127616
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1668]	train's multi_logloss: 2.88217e-07	valid's multi_logloss: 0.127622
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1669]	train's multi_logloss: 2.88072e-07	valid's multi_logloss: 0.12762
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1670]	train's multi_logloss: 2.87912e-07	valid's multi_logloss: 0.127626
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1671]	train's multi_logloss: 2.87786e-07	valid's multi_logloss: 0.127634
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1672]	train's multi_logloss: 2.87563e-07	valid's multi_logloss: 0.127646
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1673]	train's multi_logloss: 2.87445e-07	valid's multi_logloss: 0.12765
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1674]	train's multi_logloss: 2.87331e-07	valid's multi_logloss: 0.127657
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1675]	train's multi_logloss: 2.87177e-07	valid's multi_logloss: 0.12765
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1676]	train's multi_logloss: 2.87048e-07	valid's multi_logloss: 0.127653
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1677]	train's multi_logloss: 2.86829e-07	valid's multi_logloss: 0.127661
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1678]	train's multi_logloss: 2.86691e-07	valid's multi_logloss: 0.127656
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1679]	train's multi_logloss: 2.86574e-07	valid's multi_logloss: 0.127658
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1680]	train's multi_logloss: 2.86466e-07	valid's multi_logloss: 0.127661
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1681]	train's multi_logloss: 2.86312e-07	valid's multi_logloss: 0.127662
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1682]	train's multi_logloss: 2.86202e-07	valid's multi_logloss: 0.127664
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1683]	train's multi_logloss: 2.8607e-07	valid's multi_logloss: 0.127669
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1684]	train's multi_logloss: 2.85929e-07	valid's multi_logloss: 0.127671
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1685]	train's multi_logloss: 2.85802e-07	valid's multi_logloss: 0.127672
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1686]	train's multi_logloss: 2.85608e-07	valid's multi_logloss: 0.12768
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1687]	train's multi_logloss: 2.85501e-07	valid's multi_logloss: 0.127686
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1688]	train's multi_logloss: 2.85312e-07	valid's multi_logloss: 0.1277
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1689]	train's multi_logloss: 2.85166e-07	valid's multi_logloss: 0.127705
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1690]	train's multi_logloss: 2.85041e-07	valid's multi_logloss: 0.12771
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1691]	train's multi_logloss: 2.84923e-07	valid's multi_logloss: 0.127716
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1692]	train's multi_logloss: 2.84761e-07	valid's multi_logloss: 0.127708
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1693]	train's multi_logloss: 2.8461e-07	valid's multi_logloss: 0.127713
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1694]	train's multi_logloss: 2.84478e-07	valid's multi_logloss: 0.127715
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1695]	train's multi_logloss: 2.84341e-07	valid's multi_logloss: 0.127721
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1696]	train's multi_logloss: 2.84127e-07	valid's multi_logloss: 0.127732
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1697]	train's multi_logloss: 2.84002e-07	valid's multi_logloss: 0.127731
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1698]	train's multi_logloss: 2.83886e-07	valid's multi_logloss: 0.127737
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1699]	train's multi_logloss: 2.83748e-07	valid's multi_logloss: 0.127742
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1700]	train's multi_logloss: 2.83646e-07	valid's multi_logloss: 0.127744
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1701]	train's multi_logloss: 2.83518e-07	valid's multi_logloss: 0.127747
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1702]	train's multi_logloss: 2.8338e-07	valid's multi_logloss: 0.127748
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1703]	train's multi_logloss: 2.83184e-07	valid's multi_logloss: 0.127756
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1704]	train's multi_logloss: 2.83064e-07	valid's multi_logloss: 0.12775
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1705]	train's multi_logloss: 2.82961e-07	valid's multi_logloss: 0.127756
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1706]	train's multi_logloss: 2.82854e-07	valid's multi_logloss: 0.127754
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1707]	train's multi_logloss: 2.82742e-07	valid's multi_logloss: 0.127752
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1708]	train's multi_logloss: 2.82605e-07	valid's multi_logloss: 0.127746
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1709]	train's multi_logloss: 2.82492e-07	valid's multi_logloss: 0.127754
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1710]	train's multi_logloss: 2.82348e-07	valid's multi_logloss: 0.12776
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1711]	train's multi_logloss: 2.82238e-07	valid's multi_logloss: 0.127761
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1712]	train's multi_logloss: 2.82085e-07	valid's multi_logloss: 0.127762
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1713]	train's multi_logloss: 2.81989e-07	valid's multi_logloss: 0.127763
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1714]	train's multi_logloss: 2.81862e-07	valid's multi_logloss: 0.127761
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1715]	train's multi_logloss: 2.81733e-07	valid's multi_logloss: 0.127758
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1716]	train's multi_logloss: 2.8159e-07	valid's multi_logloss: 0.127763
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1717]	train's multi_logloss: 2.81487e-07	valid's multi_logloss: 0.127762
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1718]	train's multi_logloss: 2.81341e-07	valid's multi_logloss: 0.127762
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1719]	train's multi_logloss: 2.81209e-07	valid's multi_logloss: 0.127763
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1720]	train's multi_logloss: 2.81098e-07	valid's multi_logloss: 0.127772
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1721]	train's multi_logloss: 2.80976e-07	valid's multi_logloss: 0.127773
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1722]	train's multi_logloss: 2.80862e-07	valid's multi_logloss: 0.127775
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1723]	train's multi_logloss: 2.80742e-07	valid's multi_logloss: 0.127777
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1724]	train's multi_logloss: 2.80615e-07	valid's multi_logloss: 0.127782
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1725]	train's multi_logloss: 2.80404e-07	valid's multi_logloss: 0.127785
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1726]	train's multi_logloss: 2.80293e-07	valid's multi_logloss: 0.127792
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1727]	train's multi_logloss: 2.80153e-07	valid's multi_logloss: 0.127797
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1728]	train's multi_logloss: 2.80014e-07	valid's multi_logloss: 0.127794
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1729]	train's multi_logloss: 2.79885e-07	valid's multi_logloss: 0.127804
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1730]	train's multi_logloss: 2.7978e-07	valid's multi_logloss: 0.127802
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1731]	train's multi_logloss: 2.79591e-07	valid's multi_logloss: 0.127811
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1732]	train's multi_logloss: 2.79465e-07	valid's multi_logloss: 0.127817
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1733]	train's multi_logloss: 2.79278e-07	valid's multi_logloss: 0.127826
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1734]	train's multi_logloss: 2.79164e-07	valid's multi_logloss: 0.12782
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1735]	train's multi_logloss: 2.79038e-07	valid's multi_logloss: 0.127821
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1736]	train's multi_logloss: 2.78939e-07	valid's multi_logloss: 0.127829
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1737]	train's multi_logloss: 2.78811e-07	valid's multi_logloss: 0.12783
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1738]	train's multi_logloss: 2.78692e-07	valid's multi_logloss: 0.127832
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1739]	train's multi_logloss: 2.78566e-07	valid's multi_logloss: 0.127839
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1740]	train's multi_logloss: 2.78443e-07	valid's multi_logloss: 0.127843
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1741]	train's multi_logloss: 2.78333e-07	valid's multi_logloss: 0.127843
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1742]	train's multi_logloss: 2.78244e-07	valid's multi_logloss: 0.127842
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1743]	train's multi_logloss: 2.7812e-07	valid's multi_logloss: 0.127839
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1744]	train's multi_logloss: 2.7801e-07	valid's multi_logloss: 0.12784
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1745]	train's multi_logloss: 2.77864e-07	valid's multi_logloss: 0.127839
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1746]	train's multi_logloss: 2.77729e-07	valid's multi_logloss: 0.127836
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1747]	train's multi_logloss: 2.77624e-07	valid's multi_logloss: 0.127843
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1748]	train's multi_logloss: 2.77497e-07	valid's multi_logloss: 0.127848
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1749]	train's multi_logloss: 2.77396e-07	valid's multi_logloss: 0.127846
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1750]	train's multi_logloss: 2.77283e-07	valid's multi_logloss: 0.127855
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1751]	train's multi_logloss: 2.77099e-07	valid's multi_logloss: 0.127858
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1752]	train's multi_logloss: 2.77003e-07	valid's multi_logloss: 0.127865
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1753]	train's multi_logloss: 2.7689e-07	valid's multi_logloss: 0.127874
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1754]	train's multi_logloss: 2.76774e-07	valid's multi_logloss: 0.127876
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1755]	train's multi_logloss: 2.76559e-07	valid's multi_logloss: 0.127881
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1756]	train's multi_logloss: 2.76438e-07	valid's multi_logloss: 0.127888
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1757]	train's multi_logloss: 2.76323e-07	valid's multi_logloss: 0.127895
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1758]	train's multi_logloss: 2.76173e-07	valid's multi_logloss: 0.127891
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1759]	train's multi_logloss: 2.76091e-07	valid's multi_logloss: 0.127895
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1760]	train's multi_logloss: 2.75942e-07	valid's multi_logloss: 0.127891
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1761]	train's multi_logloss: 2.7584e-07	valid's multi_logloss: 0.127904
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1762]	train's multi_logloss: 2.75748e-07	valid's multi_logloss: 0.127911
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1763]	train's multi_logloss: 2.75631e-07	valid's multi_logloss: 0.127913
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1764]	train's multi_logloss: 2.75526e-07	valid's multi_logloss: 0.127909
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1765]	train's multi_logloss: 2.75428e-07	valid's multi_logloss: 0.127907
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1766]	train's multi_logloss: 2.7532e-07	valid's multi_logloss: 0.127909
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1767]	train's multi_logloss: 2.7518e-07	valid's multi_logloss: 0.127908
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1768]	train's multi_logloss: 2.75051e-07	valid's multi_logloss: 0.127905
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1769]	train's multi_logloss: 2.74949e-07	valid's multi_logloss: 0.1279
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1770]	train's multi_logloss: 2.7485e-07	valid's multi_logloss: 0.127907
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1771]	train's multi_logloss: 2.74756e-07	valid's multi_logloss: 0.12791
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1772]	train's multi_logloss: 2.74623e-07	valid's multi_logloss: 0.127911
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1773]	train's multi_logloss: 2.74517e-07	valid's multi_logloss: 0.127913
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1774]	train's multi_logloss: 2.74327e-07	valid's multi_logloss: 0.127914
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1775]	train's multi_logloss: 2.74216e-07	valid's multi_logloss: 0.127923
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1776]	train's multi_logloss: 2.7409e-07	valid's multi_logloss: 0.12792
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1777]	train's multi_logloss: 2.73977e-07	valid's multi_logloss: 0.127925
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1778]	train's multi_logloss: 2.73897e-07	valid's multi_logloss: 0.127929
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1779]	train's multi_logloss: 2.73793e-07	valid's multi_logloss: 0.127937
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1780]	train's multi_logloss: 2.73681e-07	valid's multi_logloss: 0.127938
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1781]	train's multi_logloss: 2.73546e-07	valid's multi_logloss: 0.127935
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1782]	train's multi_logloss: 2.73459e-07	valid's multi_logloss: 0.127938
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1783]	train's multi_logloss: 2.73333e-07	valid's multi_logloss: 0.127936
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1784]	train's multi_logloss: 2.73212e-07	valid's multi_logloss: 0.127937
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1785]	train's multi_logloss: 2.73039e-07	valid's multi_logloss: 0.127945
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1786]	train's multi_logloss: 2.72939e-07	valid's multi_logloss: 0.12795
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1787]	train's multi_logloss: 2.72852e-07	valid's multi_logloss: 0.12795
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1788]	train's multi_logloss: 2.72752e-07	valid's multi_logloss: 0.127952
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1789]	train's multi_logloss: 2.72653e-07	valid's multi_logloss: 0.127954
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1790]	train's multi_logloss: 2.72448e-07	valid's multi_logloss: 0.12796
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1791]	train's multi_logloss: 2.7233e-07	valid's multi_logloss: 0.127958
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1792]	train's multi_logloss: 2.72236e-07	valid's multi_logloss: 0.127964
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1793]	train's multi_logloss: 2.72139e-07	valid's multi_logloss: 0.127969
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1794]	train's multi_logloss: 2.72022e-07	valid's multi_logloss: 0.12797
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1795]	train's multi_logloss: 2.71893e-07	valid's multi_logloss: 0.127974
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1796]	train's multi_logloss: 2.71785e-07	valid's multi_logloss: 0.127976
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1797]	train's multi_logloss: 2.71669e-07	valid's multi_logloss: 0.127983
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1798]	train's multi_logloss: 2.71572e-07	valid's multi_logloss: 0.127985
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1799]	train's multi_logloss: 2.71397e-07	valid's multi_logloss: 0.127998
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1800]	train's multi_logloss: 2.71311e-07	valid's multi_logloss: 0.127998
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1801]	train's multi_logloss: 2.71217e-07	valid's multi_logloss: 0.128006
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1802]	train's multi_logloss: 2.71132e-07	valid's multi_logloss: 0.128012
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1803]	train's multi_logloss: 2.70969e-07	valid's multi_logloss: 0.128018
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1804]	train's multi_logloss: 2.70885e-07	valid's multi_logloss: 0.128023
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1805]	train's multi_logloss: 2.70809e-07	valid's multi_logloss: 0.128024
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1806]	train's multi_logloss: 2.70706e-07	valid's multi_logloss: 0.128019
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1807]	train's multi_logloss: 2.70545e-07	valid's multi_logloss: 0.128025
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1808]	train's multi_logloss: 2.70388e-07	valid's multi_logloss: 0.128037
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1809]	train's multi_logloss: 2.70306e-07	valid's multi_logloss: 0.128037
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1810]	train's multi_logloss: 2.7015e-07	valid's multi_logloss: 0.128046
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1811]	train's multi_logloss: 2.70059e-07	valid's multi_logloss: 0.12806
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1812]	train's multi_logloss: 2.6991e-07	valid's multi_logloss: 0.128061
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1813]	train's multi_logloss: 2.69756e-07	valid's multi_logloss: 0.128067
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1814]	train's multi_logloss: 2.6967e-07	valid's multi_logloss: 0.128071
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1815]	train's multi_logloss: 2.69586e-07	valid's multi_logloss: 0.128075
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1816]	train's multi_logloss: 2.69492e-07	valid's multi_logloss: 0.128075
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1817]	train's multi_logloss: 2.69352e-07	valid's multi_logloss: 0.128087
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1818]	train's multi_logloss: 2.69212e-07	valid's multi_logloss: 0.12809
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1819]	train's multi_logloss: 2.69129e-07	valid's multi_logloss: 0.128094
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1820]	train's multi_logloss: 2.69052e-07	valid's multi_logloss: 0.1281
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1821]	train's multi_logloss: 2.68927e-07	valid's multi_logloss: 0.128106
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1822]	train's multi_logloss: 2.6884e-07	valid's multi_logloss: 0.12812
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1823]	train's multi_logloss: 2.68697e-07	valid's multi_logloss: 0.128121
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1824]	train's multi_logloss: 2.6855e-07	valid's multi_logloss: 0.128126
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1825]	train's multi_logloss: 2.68461e-07	valid's multi_logloss: 0.128134
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1826]	train's multi_logloss: 2.6831e-07	valid's multi_logloss: 0.128144
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1827]	train's multi_logloss: 2.68254e-07	valid's multi_logloss: 0.128146
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1828]	train's multi_logloss: 2.68177e-07	valid's multi_logloss: 0.128145
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1829]	train's multi_logloss: 2.68033e-07	valid's multi_logloss: 0.12815
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1830]	train's multi_logloss: 2.67948e-07	valid's multi_logloss: 0.128164
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1831]	train's multi_logloss: 2.67817e-07	valid's multi_logloss: 0.128167
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1832]	train's multi_logloss: 2.67741e-07	valid's multi_logloss: 0.128166
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1833]	train's multi_logloss: 2.676e-07	valid's multi_logloss: 0.128174
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1834]	train's multi_logloss: 2.67514e-07	valid's multi_logloss: 0.128182
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1835]	train's multi_logloss: 2.67374e-07	valid's multi_logloss: 0.128188
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1836]	train's multi_logloss: 2.67297e-07	valid's multi_logloss: 0.128192
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1837]	train's multi_logloss: 2.67215e-07	valid's multi_logloss: 0.128195
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1838]	train's multi_logloss: 2.67082e-07	valid's multi_logloss: 0.128204
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1839]	train's multi_logloss: 2.66963e-07	valid's multi_logloss: 0.128214
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1840]	train's multi_logloss: 2.6688e-07	valid's multi_logloss: 0.128218
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1841]	train's multi_logloss: 2.66793e-07	valid's multi_logloss: 0.128221
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1842]	train's multi_logloss: 2.66644e-07	valid's multi_logloss: 0.128223
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1843]	train's multi_logloss: 2.66563e-07	valid's multi_logloss: 0.128227
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1844]	train's multi_logloss: 2.66445e-07	valid's multi_logloss: 0.128236
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1845]	train's multi_logloss: 2.66373e-07	valid's multi_logloss: 0.128241
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1846]	train's multi_logloss: 2.66255e-07	valid's multi_logloss: 0.128249
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1847]	train's multi_logloss: 2.66156e-07	valid's multi_logloss: 0.128254
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1848]	train's multi_logloss: 2.66052e-07	valid's multi_logloss: 0.128257
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1849]	train's multi_logloss: 2.6591e-07	valid's multi_logloss: 0.128267
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1850]	train's multi_logloss: 2.6578e-07	valid's multi_logloss: 0.128275
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1851]	train's multi_logloss: 2.65707e-07	valid's multi_logloss: 0.128279
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1852]	train's multi_logloss: 2.6559e-07	valid's multi_logloss: 0.128288
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1853]	train's multi_logloss: 2.65451e-07	valid's multi_logloss: 0.128294
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1854]	train's multi_logloss: 2.65373e-07	valid's multi_logloss: 0.128298
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1855]	train's multi_logloss: 2.65288e-07	valid's multi_logloss: 0.1283
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1856]	train's multi_logloss: 2.65153e-07	valid's multi_logloss: 0.12831
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1857]	train's multi_logloss: 2.65075e-07	valid's multi_logloss: 0.128314
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1858]	train's multi_logloss: 2.64992e-07	valid's multi_logloss: 0.128317
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1859]	train's multi_logloss: 2.64879e-07	valid's multi_logloss: 0.128326
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1860]	train's multi_logloss: 2.64802e-07	valid's multi_logloss: 0.12833
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1861]	train's multi_logloss: 2.64656e-07	valid's multi_logloss: 0.128338
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1862]	train's multi_logloss: 2.64518e-07	valid's multi_logloss: 0.128347
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1863]	train's multi_logloss: 2.64437e-07	valid's multi_logloss: 0.12835
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1864]	train's multi_logloss: 2.64364e-07	valid's multi_logloss: 0.12836
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1865]	train's multi_logloss: 2.64233e-07	valid's multi_logloss: 0.128369
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1866]	train's multi_logloss: 2.64158e-07	valid's multi_logloss: 0.128374
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1867]	train's multi_logloss: 2.64031e-07	valid's multi_logloss: 0.128382
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1868]	train's multi_logloss: 2.6393e-07	valid's multi_logloss: 0.128385
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1869]	train's multi_logloss: 2.63816e-07	valid's multi_logloss: 0.128389
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1870]	train's multi_logloss: 2.63748e-07	valid's multi_logloss: 0.128394
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1871]	train's multi_logloss: 2.63672e-07	valid's multi_logloss: 0.128401
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1872]	train's multi_logloss: 2.63576e-07	valid's multi_logloss: 0.128404
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1873]	train's multi_logloss: 2.63458e-07	valid's multi_logloss: 0.128412
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1874]	train's multi_logloss: 2.63384e-07	valid's multi_logloss: 0.128416
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1875]	train's multi_logloss: 2.63317e-07	valid's multi_logloss: 0.128418
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1876]	train's multi_logloss: 2.6324e-07	valid's multi_logloss: 0.12842
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1877]	train's multi_logloss: 2.63173e-07	valid's multi_logloss: 0.128422
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1878]	train's multi_logloss: 2.6304e-07	valid's multi_logloss: 0.128431
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1879]	train's multi_logloss: 2.62954e-07	valid's multi_logloss: 0.128436
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1880]	train's multi_logloss: 2.62872e-07	valid's multi_logloss: 0.128443
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1881]	train's multi_logloss: 2.62785e-07	valid's multi_logloss: 0.128443
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1882]	train's multi_logloss: 2.62709e-07	valid's multi_logloss: 0.128447
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1883]	train's multi_logloss: 2.62638e-07	valid's multi_logloss: 0.128449
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1884]	train's multi_logloss: 2.62578e-07	valid's multi_logloss: 0.128457
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1885]	train's multi_logloss: 2.62493e-07	valid's multi_logloss: 0.128461
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1886]	train's multi_logloss: 2.62423e-07	valid's multi_logloss: 0.128463
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1887]	train's multi_logloss: 2.62355e-07	valid's multi_logloss: 0.128465
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1888]	train's multi_logloss: 2.6227e-07	valid's multi_logloss: 0.128469
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1889]	train's multi_logloss: 2.62206e-07	valid's multi_logloss: 0.128471
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1890]	train's multi_logloss: 2.62145e-07	valid's multi_logloss: 0.128475
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1891]	train's multi_logloss: 2.62086e-07	valid's multi_logloss: 0.128483
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1892]	train's multi_logloss: 2.62016e-07	valid's multi_logloss: 0.128485
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1893]	train's multi_logloss: 2.61952e-07	valid's multi_logloss: 0.128487
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1894]	train's multi_logloss: 2.61864e-07	valid's multi_logloss: 0.128491
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1895]	train's multi_logloss: 2.61796e-07	valid's multi_logloss: 0.128494
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1896]	train's multi_logloss: 2.61736e-07	valid's multi_logloss: 0.128497
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1897]	train's multi_logloss: 2.61674e-07	valid's multi_logloss: 0.128499
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1898]	train's multi_logloss: 2.61595e-07	valid's multi_logloss: 0.128499
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1899]	train's multi_logloss: 2.61534e-07	valid's multi_logloss: 0.128504
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1900]	train's multi_logloss: 2.61469e-07	valid's multi_logloss: 0.128508
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1901]	train's multi_logloss: 2.61409e-07	valid's multi_logloss: 0.12851
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1902]	train's multi_logloss: 2.61351e-07	valid's multi_logloss: 0.12852
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1903]	train's multi_logloss: 2.61281e-07	valid's multi_logloss: 0.12852
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1904]	train's multi_logloss: 2.61195e-07	valid's multi_logloss: 0.128523
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1905]	train's multi_logloss: 2.61129e-07	valid's multi_logloss: 0.128533
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1906]	train's multi_logloss: 2.6107e-07	valid's multi_logloss: 0.128537
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1907]	train's multi_logloss: 2.61013e-07	valid's multi_logloss: 0.128541
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1908]	train's multi_logloss: 2.6094e-07	valid's multi_logloss: 0.128548
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1909]	train's multi_logloss: 2.60871e-07	valid's multi_logloss: 0.128548
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1910]	train's multi_logloss: 2.60793e-07	valid's multi_logloss: 0.128552
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1911]	train's multi_logloss: 2.6069e-07	valid's multi_logloss: 0.128553
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1912]	train's multi_logloss: 2.60613e-07	valid's multi_logloss: 0.128559
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1913]	train's multi_logloss: 2.60534e-07	valid's multi_logloss: 0.128565
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1914]	train's multi_logloss: 2.60421e-07	valid's multi_logloss: 0.128572
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1915]	train's multi_logloss: 2.60356e-07	valid's multi_logloss: 0.128581
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1916]	train's multi_logloss: 2.60295e-07	valid's multi_logloss: 0.128583
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1917]	train's multi_logloss: 2.6024e-07	valid's multi_logloss: 0.128588
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1918]	train's multi_logloss: 2.60175e-07	valid's multi_logloss: 0.128592
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1919]	train's multi_logloss: 2.60099e-07	valid's multi_logloss: 0.128599
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1920]	train's multi_logloss: 2.59978e-07	valid's multi_logloss: 0.128603
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1921]	train's multi_logloss: 2.59901e-07	valid's multi_logloss: 0.128605
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1922]	train's multi_logloss: 2.59833e-07	valid's multi_logloss: 0.128613
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1923]	train's multi_logloss: 2.59767e-07	valid's multi_logloss: 0.128617
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1924]	train's multi_logloss: 2.59704e-07	valid's multi_logloss: 0.128625
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1925]	train's multi_logloss: 2.59586e-07	valid's multi_logloss: 0.128628
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1926]	train's multi_logloss: 2.59511e-07	valid's multi_logloss: 0.128631
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1927]	train's multi_logloss: 2.59448e-07	valid's multi_logloss: 0.128638
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1928]	train's multi_logloss: 2.59331e-07	valid's multi_logloss: 0.128641
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1929]	train's multi_logloss: 2.59255e-07	valid's multi_logloss: 0.128644
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1930]	train's multi_logloss: 2.59176e-07	valid's multi_logloss: 0.128644
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1931]	train's multi_logloss: 2.59078e-07	valid's multi_logloss: 0.128646
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1932]	train's multi_logloss: 2.59021e-07	valid's multi_logloss: 0.128656
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1933]	train's multi_logloss: 2.58957e-07	valid's multi_logloss: 0.128658
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1934]	train's multi_logloss: 2.58875e-07	valid's multi_logloss: 0.128661
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1935]	train's multi_logloss: 2.58761e-07	valid's multi_logloss: 0.128668
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1936]	train's multi_logloss: 2.58672e-07	valid's multi_logloss: 0.128665
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1937]	train's multi_logloss: 2.58619e-07	valid's multi_logloss: 0.128672
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1938]	train's multi_logloss: 2.58565e-07	valid's multi_logloss: 0.128679
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1939]	train's multi_logloss: 2.58482e-07	valid's multi_logloss: 0.128685
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1940]	train's multi_logloss: 2.58418e-07	valid's multi_logloss: 0.128691
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1941]	train's multi_logloss: 2.58344e-07	valid's multi_logloss: 0.128691
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1942]	train's multi_logloss: 2.58236e-07	valid's multi_logloss: 0.128688
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1943]	train's multi_logloss: 2.58128e-07	valid's multi_logloss: 0.128697
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1944]	train's multi_logloss: 2.58075e-07	valid's multi_logloss: 0.128701
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1945]	train's multi_logloss: 2.58018e-07	valid's multi_logloss: 0.128709
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1946]	train's multi_logloss: 2.57962e-07	valid's multi_logloss: 0.128709
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1947]	train's multi_logloss: 2.57909e-07	valid's multi_logloss: 0.128713
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1948]	train's multi_logloss: 2.57811e-07	valid's multi_logloss: 0.128716
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1949]	train's multi_logloss: 2.57763e-07	valid's multi_logloss: 0.128711
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1950]	train's multi_logloss: 2.57631e-07	valid's multi_logloss: 0.128713
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1951]	train's multi_logloss: 2.57586e-07	valid's multi_logloss: 0.12872
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1952]	train's multi_logloss: 2.57524e-07	valid's multi_logloss: 0.12873
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1953]	train's multi_logloss: 2.57472e-07	valid's multi_logloss: 0.12873
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1954]	train's multi_logloss: 2.5742e-07	valid's multi_logloss: 0.12873
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1955]	train's multi_logloss: 2.57359e-07	valid's multi_logloss: 0.12874
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1956]	train's multi_logloss: 2.57281e-07	valid's multi_logloss: 0.12874
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1957]	train's multi_logloss: 2.57177e-07	valid's multi_logloss: 0.128737
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1958]	train's multi_logloss: 2.57076e-07	valid's multi_logloss: 0.128745
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1959]	train's multi_logloss: 2.57016e-07	valid's multi_logloss: 0.128755
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1960]	train's multi_logloss: 2.56969e-07	valid's multi_logloss: 0.128756
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1961]	train's multi_logloss: 2.56892e-07	valid's multi_logloss: 0.128757
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1962]	train's multi_logloss: 2.56832e-07	valid's multi_logloss: 0.128765
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1963]	train's multi_logloss: 2.56764e-07	valid's multi_logloss: 0.128771
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1964]	train's multi_logloss: 2.56716e-07	valid's multi_logloss: 0.128776
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1965]	train's multi_logloss: 2.56666e-07	valid's multi_logloss: 0.128782
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1966]	train's multi_logloss: 2.56553e-07	valid's multi_logloss: 0.128788
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1967]	train's multi_logloss: 2.56503e-07	valid's multi_logloss: 0.128787
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1968]	train's multi_logloss: 2.56377e-07	valid's multi_logloss: 0.128797
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1969]	train's multi_logloss: 2.56308e-07	valid's multi_logloss: 0.128807
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1970]	train's multi_logloss: 2.56236e-07	valid's multi_logloss: 0.128811
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1971]	train's multi_logloss: 2.56186e-07	valid's multi_logloss: 0.128811
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1972]	train's multi_logloss: 2.56073e-07	valid's multi_logloss: 0.12882
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1973]	train's multi_logloss: 2.56008e-07	valid's multi_logloss: 0.128826
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1974]	train's multi_logloss: 2.55891e-07	valid's multi_logloss: 0.128838
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1975]	train's multi_logloss: 2.55821e-07	valid's multi_logloss: 0.128834
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1976]	train's multi_logloss: 2.55756e-07	valid's multi_logloss: 0.128842
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1977]	train's multi_logloss: 2.55689e-07	valid's multi_logloss: 0.128851
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1978]	train's multi_logloss: 2.55578e-07	valid's multi_logloss: 0.12886
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1979]	train's multi_logloss: 2.55521e-07	valid's multi_logloss: 0.128872
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1980]	train's multi_logloss: 2.55476e-07	valid's multi_logloss: 0.128867
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1981]	train's multi_logloss: 2.55425e-07	valid's multi_logloss: 0.128875
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1982]	train's multi_logloss: 2.55339e-07	valid's multi_logloss: 0.12888
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1983]	train's multi_logloss: 2.55221e-07	valid's multi_logloss: 0.12889
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1984]	train's multi_logloss: 2.55163e-07	valid's multi_logloss: 0.128896
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1985]	train's multi_logloss: 2.55073e-07	valid's multi_logloss: 0.128904
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1986]	train's multi_logloss: 2.55028e-07	valid's multi_logloss: 0.128903
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1987]	train's multi_logloss: 2.54936e-07	valid's multi_logloss: 0.128902
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1988]	train's multi_logloss: 2.5488e-07	valid's multi_logloss: 0.12891
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1989]	train's multi_logloss: 2.54791e-07	valid's multi_logloss: 0.128901
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1990]	train's multi_logloss: 2.54719e-07	valid's multi_logloss: 0.1289
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1991]	train's multi_logloss: 2.54667e-07	valid's multi_logloss: 0.128907
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1992]	train's multi_logloss: 2.54625e-07	valid's multi_logloss: 0.128913
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1993]	train's multi_logloss: 2.54541e-07	valid's multi_logloss: 0.12891
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1994]	train's multi_logloss: 2.54459e-07	valid's multi_logloss: 0.128905
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1995]	train's multi_logloss: 2.54375e-07	valid's multi_logloss: 0.128904
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1996]	train's multi_logloss: 2.54324e-07	valid's multi_logloss: 0.128909
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1997]	train's multi_logloss: 2.54274e-07	valid's multi_logloss: 0.128915
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1998]	train's multi_logloss: 2.5421e-07	valid's multi_logloss: 0.128916
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[1999]	train's multi_logloss: 2.54169e-07	valid's multi_logloss: 0.128924
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[2000]	train's multi_logloss: 2.54039e-07	valid's multi_logloss: 0.128924


feature_importance_df = pd.DataFrame()
y_pred_1=gbm.predict(X_test)
y_pred_1 = [np.argmax(line) for line in y_pred_1]


x=gbm.feature_importance()
y=pd.DataFrame(X_train)
warnings.simplefilter(action='ignore', category=FutureWarning)

# sorted(zip(clf.feature_importances_, X.columns), reverse=True)
feature_imp = pd.DataFrame(sorted(zip(x,y)), columns=['Value','Feature'])
feature_imp.iloc[:,0] = (feature_imp.iloc[:,0]-min(feature_imp.iloc[:,0]))/(max(feature_imp.iloc[:,0])-min(feature_imp.iloc[:,0]))*100
print(feature_imp.iloc[:,:2])

plt.figure(figsize=(20, 10))
sns.barplot(y="Value", x="Feature", data=feature_imp.sort_values(by="Value", ascending=False))
plt.title('LightGBM Features (avg over folds)')
plt.tight_layout()
plt.show()
# plt.savefig('images/case-1/lgbm_importances-01.png')

         Value  Feature
0     0.000000       11
1     0.077129       21
2     0.186734       16
3     0.229358       27
4     0.274012        6
5     0.276041       14
6     0.525696       19
7     0.535845       17
8     0.588617        7
9     1.526346       12
10    1.717139       18
11    2.630511       20
12    4.169035        4
13    6.754892       25
14    7.337420        3
15    7.589104        9
16    8.191930       15
17    8.409109       26
18    9.103272        5
19   12.326459       24
20   14.072014       23
21   15.320289       10
22   17.423074       22
23   18.182187        1
24   19.172688       28
25   22.056913       13
26   26.792238        2
27   81.899001        0
28  100.000000        8


y_score =y_pred_1

# # Binarize the output
y_train = label_binarize(y_train, classes=[0, 1, 2,3,4])
# n_classes = y_train.shape[1]
y_score = label_binarize(y_score, classes=[0, 1, 2,3,4])


fpr = dict()
tpr = dict()
roc_auc = dict()

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(5):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.98889, Cohen's Kappa Score: 0.93886
Confusion Matrix:
[[824   2   0   1   0]
 [  2  60   0   0   0]
 [  0   0   4   1   0]
 [  0   0   0   2   3]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      1.00      1.00       827
           1       0.97      0.97      0.97        62
           2       1.00      0.80      0.89         5
           3       0.40      0.40      0.40         5
           4       0.00      0.00      0.00         1

    accuracy                           0.99       900
   macro avg       0.67      0.63      0.65       900
weighted avg       0.99      0.99      0.99       900


from xgboost import XGBClassifier
import lime.lime_tabular
classes=[0, 1, 2, 3, 4]
df_k=df.drop(['DAST'],axis=1)
all_feat=train.columns
print(all_feat)
model_xgb = XGBClassifier()
model_xgb.fit(X_train, y_train.argmax(axis=1))
predict_fn_xgb = lambda x: model_xgb.predict_proba(x).astype(float)
explainer = lime.lime_tabular.LimeTabularExplainer(X_train,mode='classification',feature_selection= 'auto',
                                                   class_names=classes,feature_names = all_feat, 
                                                   kernel_width=None,discretize_continuous=True)

Index(['DAST', 'ANYALC', 'BINGEDAYS', 'DRUGDAYS', 'ALCDRUGS', 'DAYSCOCAINE',
       'MARYJDAYS', 'ANYOPIATEDAYS', 'METHDAYS', 'AGE', 'COSCREEN_1', 'SEX_1',
       'SEX_2', 'HISPANIC_1', 'RACE_2', 'RACE_3', 'VET_1', 'ACTIVE_1',
       'DEPLOY_1', 'DEPLOY_2', 'DEPLOY_3', 'DEPLOY_4', 'DEPLOY_5', 'AUDIT_1',
       'AUDIT_2', 'BI_1', 'BT_1', 'RT_1', 'INJECT_1', 'TOBMONTH_1'],
      dtype='object')
[16:49:18] WARNING: ../src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'multi:softprob' was changed from 'merror' to 'mlogloss'. Explicitly set eval_metric if you'd like to restore the old behavior.


pred =model_xgb.predict(X_test)
print('model_xgb', metrics.accuracy_score(y_test.argmax(axis=1), pred))

model_xgb 0.9866666666666667


y_score =pred

# # Binarize the output
y_train = label_binarize(y_train, classes=[0, 1, 2,3,4])
# n_classes = y_train.shape[1]
y_score = label_binarize(y_score, classes=[0, 1, 2,3,4])


fpr = dict()
tpr = dict()
roc_auc = dict()

fpr = dict()
tpr = dict()
roc_auc = dict()

for i in range(5):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])

plt.figure()
lw = 2
plt.plot(fpr[2], tpr[2], color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc[2])
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()

print_stats(y_test.argmax(axis=1), y_score.argmax(axis=1))

Accuracy: 0.98667, Cohen's Kappa Score: 0.90494
Confusion Matrix:
[[823   3   0   0   1]
 [  2  60   0   0   0]
 [  0   0   4   0   1]
 [  0   0   0   1   4]
 [  0   0   0   1   0]]
Classification Report:
              precision    recall  f1-score   support

           0       1.00      1.00      1.00       827
           1       0.95      0.97      0.96        62
           2       1.00      0.80      0.89         5
           3       0.50      0.20      0.29         5
           4       0.00      0.00      0.00         1

    accuracy                           0.99       900
   macro avg       0.69      0.59      0.63       900
weighted avg       0.99      0.99      0.99       900


importance = permutation_importance(model_xgb, X_test, y_test.argmax(axis=1))
importance =importance.importances_mean
importance = (importance-min(importance))/(max(importance)-min(importance))*100
plt.figure(figsize=(20,10))
print(importance.shape)
for i,v in enumerate(importance):
    print('Feature: %0d, Score: %.5f' % (i,v))
# plot feature importance
sns.barplot([x for x in range(len(importance))], importance)
pyplot.show()

(29,)
Feature: 0, Score: 3.98724
Feature: 1, Score: 4.78469
Feature: 2, Score: 22.16906
Feature: 3, Score: 3.98724
Feature: 4, Score: 3.98724
Feature: 5, Score: 3.98724
Feature: 6, Score: 3.98724
Feature: 7, Score: 3.98724
Feature: 8, Score: 4.46571
Feature: 9, Score: 0.00000
Feature: 10, Score: 3.66826
Feature: 11, Score: 3.98724
Feature: 12, Score: 3.98724
Feature: 13, Score: 3.18979
Feature: 14, Score: 3.98724
Feature: 15, Score: 3.98724
Feature: 16, Score: 3.98724
Feature: 17, Score: 3.98724
Feature: 18, Score: 3.98724
Feature: 19, Score: 3.98724
Feature: 20, Score: 3.98724
Feature: 21, Score: 3.98724
Feature: 22, Score: 18.50080
Feature: 23, Score: 6.37959
Feature: 24, Score: 100.00000
Feature: 25, Score: 12.91866
Feature: 26, Score: 9.56938
Feature: 27, Score: 3.98724
Feature: 28, Score: 5.10367


observation_1=32
print(X_test[32])
print(y_test[32])

[0.         0.         0.         0.         0.         0.
 0.         0.         0.09459459 0.         1.         0.
 0.         1.         0.         0.         0.         0.
 0.         0.         0.         0.         0.         0.
 0.         0.         0.         0.         1.        ]
[1 0 0 0 0]


explanation = explainer.explain_instance(X_test[observation_1], predict_fn_xgb, num_features=25,top_labels=5)

explanation.show_in_notebook()


print("Explanation Local Prediction              : ", explanation.local_pred)
print("Explanation Global Prediction Probability : ", explanation.predict_proba)

Explanation Local Prediction              :  [0.86261325]
Explanation Global Prediction Probability :  [9.99879718e-01 5.59865184e-05 1.36394747e-05 3.10372779e-05
 1.96522524e-05]


y_train.argmax(axis=1).shape[0]

30000


# fit and evaluate a model
def evaluate_model(trainX, trainy, testX, testy):
    verbose, epochs, batch_size = 0, 10, 32 
    n_timesteps, n_features, n_outputs = X_train.shape[1], X_train.shape[2], y_train.shape[1]
    model = tf.keras.Sequential()
    model.add(tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu', input_shape=(n_timesteps,n_features)))
    model.add(tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu'))
    model.add(tf.keras.layers.Dropout(0.5))
    model.add(tf.keras.layers.MaxPooling1D(pool_size=2))
    model.add(tf.keras.layers.Flatten())
    model.add(tf.keras.layers.Dense(100, activation='relu'))
    model.add(tf.keras.layers.Dense(n_outputs, activation='softmax'))
    model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
    # fit network
    model.fit(trainX, trainy, epochs=epochs, batch_size=batch_size, verbose=verbose)
    # evaluate model
    _, accuracy = model.evaluate(testX, testy, batch_size=batch_size, verbose=0)
    return accuracy


# repeat experiment
X_train = X_train.reshape(X_train.shape[0], X_train.shape[1], 1)
X_test = X_test.reshape(X_test.shape[0], X_test.shape[1], 1)
scores = list()
for r in range(20):
	score = evaluate_model(X_train, y_train, X_test, y_test)
	score = score * 100.0
	print('>#%d: %.3f' % (r+1, score))
	scores.append(score)

>#1: 98.667
>#2: 98.111
>#3: 98.778
>#4: 98.000
>#5: 98.778
>#6: 98.778
>#7: 98.000
>#8: 97.778
>#9: 97.889
>#10: 98.000
>#11: 97.556
>#12: 98.444
>#13: 97.667
>#14: 98.667
>#15: 98.556
>#16: 97.444
>#17: 97.778
>#18: 98.111
>#19: 98.556
>#20: 98.444


def summarize_results(scores, params):
	print(scores, params)
	# summarize mean and standard deviation
	for i in range(len(scores)):
		m, s = mean(scores[i]), std(scores[i])
		print('Param=%s: %.3f%% (+/-%.3f)' % (params[i], m, s))
	# boxplot of scores
	pyplot.boxplot(scores, labels=params)

 

def scale_data(trainX, testX, standardize):
	# remove overlap
	cut = int(trainX.shape[1] / 2)
	longX = trainX[:, -cut:, :]
	# flatten windows
	longX = longX.reshape((longX.shape[0] * longX.shape[1], longX.shape[2]))
	# flatten train and test
	flatTrainX = trainX.reshape((trainX.shape[0] * trainX.shape[1], trainX.shape[2]))
	flatTestX = testX.reshape((testX.shape[0] * testX.shape[1], testX.shape[2]))
	# standardize
	if standardize:
		s = StandardScaler()
		# fit on training data
		s.fit(longX)
		# apply to training and test data
		longX = s.transform(longX)
		flatTrainX = s.transform(flatTrainX)
		flatTestX = s.transform(flatTestX)
	# reshape
	flatTrainX = flatTrainX.reshape((trainX.shape))
	flatTestX = flatTestX.reshape((testX.shape))
	return flatTrainX, flatTestX

def evaluate_model(trainX, trainy, testX, testy, param):
    verbose, epochs, batch_size = 0, 10, 32
    n_timesteps, n_features, n_outputs = trainX.shape[1], trainX.shape[2], trainy.shape[1]
    # scale data
    trainX, testX = scale_data(trainX, testX, param)
    model = tf.keras.Sequential()
    model.add(tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu', input_shape=(n_timesteps,n_features)))
    model.add(tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu'))
    model.add(tf.keras.layers.Dropout(0.5))
    model.add(tf.keras.layers.MaxPooling1D(pool_size=2))
    model.add(tf.keras.layers.Flatten())
    model.add(tf.keras.layers.Dense(100, activation='relu'))
    model.add(tf.keras.layers.Dense(n_outputs, activation='softmax'))
    model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
    # fit network
    model.fit(trainX, trainy, epochs=epochs, batch_size=batch_size, verbose=verbose)
	# evaluate model
    _, accuracy = model.evaluate(testX, testy, batch_size=batch_size, verbose=0)
    return accuracy

def run_experiment(params, repeats=10):
	# load data

	# test each parameter
	all_scores = list()
	for p in params:
		# repeat experiment
		scores = list()
		for r in range(repeats):
			score = evaluate_model(X_train, y_train, X_test, y_test, p)
			score = score * 100.0
			print('>p=%s #%d: %.3f' % (p, r+1, score))
			scores.append(score)
		all_scores.append(scores)
	# summarize results
	summarize_results(all_scores, params)
 
# run the experiment
n_params = [False, True]
run_experiment(n_params)

>p=False #1: 97.556
>p=False #2: 98.667
>p=False #3: 98.222
>p=False #4: 98.667
>p=False #5: 98.000
>p=False #6: 98.222
>p=False #7: 97.444
>p=False #8: 98.000
>p=False #9: 98.333
>p=False #10: 97.778
>p=True #1: 98.889
>p=True #2: 97.778
>p=True #3: 98.444
>p=True #4: 97.667
>p=True #5: 98.889
>p=True #6: 98.333
>p=True #7: 98.222
>p=True #8: 97.444
>p=True #9: 97.556
>p=True #10: 98.333
[[97.55555391311646, 98.66666793823242, 98.22221994400024, 98.66666793823242, 98.00000190734863, 98.22221994400024, 97.44444489479065, 98.00000190734863, 98.33333492279053, 97.77777791023254], [98.88888597488403, 97.77777791023254, 98.44444394111633, 97.66666889190674, 98.88888597488403, 98.33333492279053, 98.22221994400024, 97.44444489479065, 97.55555391311646, 98.33333492279053]] [False, True]
Param=False: 98.089% (+/-0.397)
Param=True: 98.156% (+/-0.497)


# fit and evaluate a model
def evaluate_model(trainX, trainy, testX, testy, n_filters):
    verbose, epochs, batch_size = 0, 10, 32
    n_timesteps, n_features, n_outputs = trainX.shape[1], trainX.shape[2], trainy.shape[1]
    model = tf.keras.Sequential()
    model.add(tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu', input_shape=(n_timesteps,n_features)))
    model.add(tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu'))
    model.add(tf.keras.layers.Dropout(0.5))
    model.add(tf.keras.layers.MaxPooling1D(pool_size=2))
    model.add(tf.keras.layers.Flatten())
    model.add(tf.keras.layers.Dense(100, activation='relu'))
    model.add(tf.keras.layers.Dense(n_outputs, activation='softmax'))
    model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
	# fit network
    model.fit(trainX, trainy, epochs=epochs, batch_size=batch_size, verbose=verbose)
    # evaluate model
    _, accuracy = model.evaluate(testX, testy, batch_size=batch_size, verbose=0)
    return accuracy
 
# summarize scores
def summarize_results(scores, params):
	print(scores, params)
	# summarize mean and standard deviation
	for i in range(len(scores)):
		m, s = mean(scores[i]), std(scores[i])
		print('Param=%d: %.3f%% (+/-%.3f)' % (params[i], m, s))
	# boxplot of scores
	pyplot.boxplot(scores, labels=params)
	pyplot.savefig('exp_cnn_filters.png')
 
# run an experiment
def run_experiment(params, repeats=10):
	# test each parameter
	all_scores = list()
	for p in params:
		# repeat experiment
		scores = list()
		for r in range(repeats):
			score = evaluate_model(X_train, y_train, X_test, y_test, p)
			score = score * 100.0
			print('>p=%d #%d: %.3f' % (p, r+1, score))
			scores.append(score)
		all_scores.append(scores)
	# summarize results
	summarize_results(all_scores, params)
 
# run the experiment
n_params = [8, 16, 32, 64, 128, 256]
run_experiment(n_params)

>p=8 #1: 97.889
>p=8 #2: 98.000
>p=8 #3: 98.111
>p=8 #4: 97.667
>p=8 #5: 96.889
>p=8 #6: 99.000
>p=8 #7: 98.444
>p=8 #8: 97.889
>p=8 #9: 97.333
>p=8 #10: 97.778
>p=16 #1: 98.333
>p=16 #2: 97.889
>p=16 #3: 97.667
>p=16 #4: 98.556
>p=16 #5: 98.667
>p=16 #6: 98.444
>p=16 #7: 99.000
>p=16 #8: 98.111
>p=16 #9: 98.111
>p=16 #10: 98.000
>p=32 #1: 97.556
>p=32 #2: 97.333
>p=32 #3: 97.778
>p=32 #4: 99.000
>p=32 #5: 98.556
>p=32 #6: 98.778
>p=32 #7: 98.000
>p=32 #8: 98.000
>p=32 #9: 97.556
>p=32 #10: 98.889
>p=64 #1: 98.000
>p=64 #2: 97.222
>p=64 #3: 97.444
>p=64 #4: 97.889
>p=64 #5: 98.222
>p=64 #6: 98.667
>p=64 #7: 98.222
>p=64 #8: 97.889
>p=64 #9: 98.000
>p=64 #10: 97.778
>p=128 #1: 98.222
>p=128 #2: 98.000
>p=128 #3: 98.333
>p=128 #4: 98.444
>p=128 #5: 98.333
>p=128 #6: 98.000
>p=128 #7: 97.333
>p=128 #8: 99.000
>p=128 #9: 97.778
>p=128 #10: 97.778
>p=256 #1: 98.778
>p=256 #2: 98.111
>p=256 #3: 98.889
>p=256 #4: 98.222
>p=256 #5: 97.778
>p=256 #6: 97.778
>p=256 #7: 97.333
>p=256 #8: 96.889
>p=256 #9: 98.333
>p=256 #10: 98.889
[[97.88888692855835, 98.00000190734863, 98.11111092567444, 97.66666889190674, 96.88888788223267, 99.00000095367432, 98.44444394111633, 97.88888692855835, 97.33333587646484, 97.77777791023254], [98.33333492279053, 97.88888692855835, 97.66666889190674, 98.55555295944214, 98.66666793823242, 98.44444394111633, 99.00000095367432, 98.11111092567444, 98.11111092567444, 98.00000190734863], [97.55555391311646, 97.33333587646484, 97.77777791023254, 99.00000095367432, 98.55555295944214, 98.77777695655823, 98.00000190734863, 98.00000190734863, 97.55555391311646, 98.88888597488403], [98.00000190734863, 97.22222089767456, 97.44444489479065, 97.88888692855835, 98.22221994400024, 98.66666793823242, 98.22221994400024, 97.88888692855835, 98.00000190734863, 97.77777791023254], [98.22221994400024, 98.00000190734863, 98.33333492279053, 98.44444394111633, 98.33333492279053, 98.00000190734863, 97.33333587646484, 99.00000095367432, 97.77777791023254, 97.77777791023254], [98.77777695655823, 98.11111092567444, 98.88888597488403, 98.22221994400024, 97.77777791023254, 97.77777791023254, 97.33333587646484, 96.88888788223267, 98.33333492279053, 98.88888597488403]] [8, 16, 32, 64, 128, 256]
Param=8: 97.900% (+/-0.545)
Param=16: 98.278% (+/-0.379)
Param=32: 98.144% (+/-0.582)
Param=64: 97.933% (+/-0.386)
Param=128: 98.122% (+/-0.432)
Param=256: 98.100% (+/-0.635)


def evaluate_model(trainX, trainy, testX, testy, n_kernel):
    verbose, epochs, batch_size = 0, 15, 32
    n_timesteps, n_features, n_outputs = trainX.shape[1], trainX.shape[2], trainy.shape[1]
    model = tf.keras.Sequential()
    model.add(tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu', input_shape=(n_timesteps,n_features)))
    model.add(tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu'))
    model.add(tf.keras.layers.Dropout(0.5))
    model.add(tf.keras.layers.MaxPooling1D(pool_size=2))
    model.add(tf.keras.layers.Flatten())
    model.add(tf.keras.layers.Dense(100, activation='relu'))
    model.add(tf.keras.layers.Dense(n_outputs, activation='softmax'))
    model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
	# fit network
    model.fit(trainX, trainy, epochs=epochs, batch_size=batch_size, verbose=verbose)
	# evaluate model
    _, accuracy = model.evaluate(testX, testy, batch_size=batch_size, verbose=0)
    return accuracy
 
# summarize scores
def summarize_results(scores, params):
	print(scores, params)
	# summarize mean and standard deviation
	for i in range(len(scores)):
		m, s = mean(scores[i]), std(scores[i])
		print('Param=%d: %.3f%% (+/-%.3f)' % (params[i], m, s))
	# boxplot of scores
	pyplot.boxplot(scores, labels=params)
	pyplot.savefig('exp_cnn_kernel.png')
 
# run an experiment
def run_experiment(params, repeats=10):

	# test each parameter
	all_scores = list()
	for p in params:
		# repeat experiment
		scores = list()
		for r in range(repeats):
			score = evaluate_model(X_train, y_train, X_test, y_test, p)
			score = score * 100.0
			print('>p=%d #%d: %.3f' % (p, r+1, score))
			scores.append(score)
		all_scores.append(scores)
	# summarize results
	summarize_results(all_scores, params)
 
# run the experiment
n_params = [2, 3, 5, 7, 11]
run_experiment(n_params)

>p=2 #1: 98.222
>p=2 #2: 98.556
>p=2 #3: 98.556
>p=2 #4: 98.667
>p=2 #5: 97.889
>p=2 #6: 98.333
>p=2 #7: 98.889
>p=2 #8: 97.889
>p=2 #9: 97.889
>p=2 #10: 98.222
>p=3 #1: 97.556
>p=3 #2: 98.222
>p=3 #3: 98.778
>p=3 #4: 98.000
>p=3 #5: 97.778
>p=3 #6: 98.222
>p=3 #7: 98.778
>p=3 #8: 98.444
>p=3 #9: 97.444
>p=3 #10: 97.889
>p=5 #1: 98.667
>p=5 #2: 97.667
>p=5 #3: 98.000
>p=5 #4: 97.778
>p=5 #5: 97.778
>p=5 #6: 97.778
>p=5 #7: 97.667
>p=5 #8: 98.778
>p=5 #9: 98.333
>p=5 #10: 98.000
>p=7 #1: 98.556
>p=7 #2: 98.889
>p=7 #3: 98.000
>p=7 #4: 98.556
>p=7 #5: 97.444
>p=7 #6: 97.889
>p=7 #7: 98.000
>p=7 #8: 98.222
>p=7 #9: 98.000
>p=7 #10: 97.667
>p=11 #1: 98.889
>p=11 #2: 97.889
>p=11 #3: 97.444
>p=11 #4: 98.111
>p=11 #5: 99.111
>p=11 #6: 99.111
>p=11 #7: 99.111
>p=11 #8: 97.556
>p=11 #9: 98.111
>p=11 #10: 97.778
[[98.22221994400024, 98.55555295944214, 98.55555295944214, 98.66666793823242, 97.88888692855835, 98.33333492279053, 98.88888597488403, 97.88888692855835, 97.88888692855835, 98.22221994400024], [97.55555391311646, 98.22221994400024, 98.77777695655823, 98.00000190734863, 97.77777791023254, 98.22221994400024, 98.77777695655823, 98.44444394111633, 97.44444489479065, 97.88888692855835], [98.66666793823242, 97.66666889190674, 98.00000190734863, 97.77777791023254, 97.77777791023254, 97.77777791023254, 97.66666889190674, 98.77777695655823, 98.33333492279053, 98.00000190734863], [98.55555295944214, 98.88888597488403, 98.00000190734863, 98.55555295944214, 97.44444489479065, 97.88888692855835, 98.00000190734863, 98.22221994400024, 98.00000190734863, 97.66666889190674], [98.88888597488403, 97.88888692855835, 97.44444489479065, 98.11111092567444, 99.11110997200012, 99.11110997200012, 99.11110997200012, 97.55555391311646, 98.11111092567444, 97.77777791023254]] [2, 3, 5, 7, 11]
Param=2: 98.311% (+/-0.336)
Param=3: 98.111% (+/-0.442)
Param=5: 98.044% (+/-0.389)
Param=7: 98.122% (+/-0.417)
Param=11: 98.311% (+/-0.642)


# fit and evaluate a model
import keras
from keras.utils.vis_utils import plot_model
def evaluate_model(trainX, trainy, testX, testy):
	verbose, epochs, batch_size = 0, 10, 32
	n_timesteps, n_features, n_outputs = trainX.shape[1], trainX.shape[2], trainy.shape[1]
 	# head 1
	inputs1 = tf.keras.Input(shape=(n_timesteps,n_features))
	conv1 = tf.keras.layers.Conv1D(filters=64, kernel_size=3, activation='relu')(inputs1)
	drop1 = tf.keras.layers.Dropout(0.5)(conv1)
	pool1 = tf.keras.layers.MaxPooling1D(pool_size=2)(drop1)
	flat1 = tf.keras.layers.Flatten()(pool1)
	# head 2
	inputs2 = tf.keras.Input(shape=(n_timesteps,n_features))
	conv2 = tf.keras.layers.Conv1D(filters=64, kernel_size=5, activation='relu')(inputs2)
	drop2 = tf.keras.layers.Dropout(0.5)(conv2)
	pool2 = tf.keras.layers.MaxPooling1D(pool_size=2)(drop2)
	flat2 = tf.keras.layers.Flatten()(pool2)
	# head 3
	inputs3 = tf.keras.Input(shape=(n_timesteps,n_features))
	conv3 = tf.keras.layers.Conv1D(filters=64, kernel_size=11, activation='relu')(inputs3)
	drop3 = tf.keras.layers.Dropout(0.5)(conv3)
	pool3 = tf.keras.layers.MaxPooling1D(pool_size=2)(drop3)
	flat3 = tf.keras.layers.Flatten()(pool3)
	# merge
	merged = keras.layers.merge.concatenate([flat1, flat2, flat3])
	# interpretation
	dense1 = tf.keras.layers.Dense(100, activation='relu')(merged)
	outputs = tf.keras.layers.Dense(n_outputs, activation='softmax')(dense1)
	model = tf.keras.Model(inputs=[inputs1, inputs2, inputs3], outputs=outputs)
	# save a plot of the model
	plot_model(model, show_shapes=True, to_file='multichannel.png')
	model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
	# fit network
	model.fit([trainX,trainX,trainX], trainy, epochs=epochs, batch_size=batch_size, verbose=verbose)
	# evaluate model
	_, accuracy = model.evaluate([testX,testX,testX], testy, batch_size=batch_size, verbose=0)
	return accuracy
 
# summarize scores
def summarize_results(scores):
	print(scores)
	m, s = mean(scores), std(scores)
	print('Accuracy: %.3f%% (+/-%.3f)' % (m, s))
 
# run an experiment
def run_experiment(repeats=10):

	scores = list()
	for r in range(repeats):
		score = evaluate_model(X_train, y_train, X_test, y_test)
		score = score * 100.0
		print('>#%d: %.3f' % (r+1, score))
		scores.append(score)
	# summarize results
	summarize_results(scores)
 
# run the experiment
run_experiment()

>#1: 97.111
>#2: 99.000
>#3: 97.333
>#4: 97.556
>#5: 97.778
>#6: 97.778
>#7: 97.333
>#8: 98.556
>#9: 97.444
>#10: 97.778
[97.11111187934875, 99.00000095367432, 97.33333587646484, 97.55555391311646, 97.77777791023254, 97.77777791023254, 97.33333587646484, 98.55555295944214, 97.44444489479065, 97.77777791023254]
Accuracy: 97.767% (+/-0.557)


hidden_units = [100, 100]
learning_rate = 0.003
dropout_rate = 0.05
num_epochs =500
batch_size = 100


def run_experiment(model, x_train, y_train):
    # Compile the model.
    model.compile(
        optimizer=tf.keras.optimizers.Adam(learning_rate),
        loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
        metrics=[tf.keras.metrics.SparseCategoricalAccuracy(name="acc")],
    )
    # Create an early stopping callback.
    early_stopping = tf.keras.callbacks.EarlyStopping(
        monitor="val_acc", patience=50, restore_best_weights=True
    )
    # Fit the model.
    history = model.fit(
        x=x_train,
        y=y_train,
        epochs=num_epochs,
        batch_size=batch_size,
        validation_split=0.25,
        callbacks=[early_stopping],
    )

    return history


def display_learning_curves(history):
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 5))

    ax1.plot(history.history["loss"])
    ax1.plot(history.history["val_loss"])
    ax1.legend(["train", "test"], loc="upper right")
    ax1.set_xlabel("Epochs")
    ax1.set_ylabel("Loss")

    ax2.plot(history.history["acc"])
    ax2.plot(history.history["val_acc"])
    ax2.legend(["train", "test"], loc="upper right")
    ax2.set_xlabel("Epochs")
    ax2.set_ylabel("Accuracy")
    plt.show()


def create_ffn(hidden_units, dropout_rate, name=None):
    fnn_layers = []

    for units in hidden_units:
        fnn_layers.append(layers.BatchNormalization())
        fnn_layers.append(layers.Dropout(dropout_rate))
        fnn_layers.append(layers.Dense(units, activation=tf.nn.relu))

    return keras.Sequential(fnn_layers, name=name)


num_classes=5
num_features=29
def create_baseline_model(hidden_units, num_classes, dropout_rate=0.2):
    inputs = layers.Input(shape=(num_features,), name="input_features")
    x = create_ffn(hidden_units, dropout_rate, name=f"ffn_block1")(inputs)
    for block_idx in range(100):
        # Create an FFN block.
        x1 = create_ffn(hidden_units, dropout_rate, name=f"ffn_block{block_idx + 2}")(x)
        # Add skip connection.
        x = layers.Add(name=f"skip_connection{block_idx + 2}")([x, x1])
    # Compute logits.
    logits = layers.Dense(num_classes, name="logits")(x)
    # Create the model.
    return keras.Model(inputs=inputs, outputs=logits, name="baseline")


baseline_model = create_baseline_model(hidden_units, num_classes, dropout_rate)
baseline_model.summary()

Model: "baseline"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_features (InputLayer)     [(None, 29)]         0                                            
__________________________________________________________________________________________________
ffn_block1 (Sequential)         (None, 100)          13616       input_features[0][0]             
__________________________________________________________________________________________________
ffn_block2 (Sequential)         (None, 100)          21000       ffn_block1[0][0]                 
__________________________________________________________________________________________________
skip_connection2 (Add)          (None, 100)          0           ffn_block1[0][0]                 
                                                                 ffn_block2[0][0]                 
__________________________________________________________________________________________________
ffn_block3 (Sequential)         (None, 100)          21000       skip_connection2[0][0]           
__________________________________________________________________________________________________
skip_connection3 (Add)          (None, 100)          0           skip_connection2[0][0]           
                                                                 ffn_block3[0][0]                 
__________________________________________________________________________________________________
ffn_block4 (Sequential)         (None, 100)          21000       skip_connection3[0][0]           
__________________________________________________________________________________________________
skip_connection4 (Add)          (None, 100)          0           skip_connection3[0][0]           
                                                                 ffn_block4[0][0]                 
__________________________________________________________________________________________________
ffn_block5 (Sequential)         (None, 100)          21000       skip_connection4[0][0]           
__________________________________________________________________________________________________
skip_connection5 (Add)          (None, 100)          0           skip_connection4[0][0]           
                                                                 ffn_block5[0][0]                 
__________________________________________________________________________________________________
ffn_block6 (Sequential)         (None, 100)          21000       skip_connection5[0][0]           
__________________________________________________________________________________________________
skip_connection6 (Add)          (None, 100)          0           skip_connection5[0][0]           
                                                                 ffn_block6[0][0]                 
__________________________________________________________________________________________________
ffn_block7 (Sequential)         (None, 100)          21000       skip_connection6[0][0]           
__________________________________________________________________________________________________
skip_connection7 (Add)          (None, 100)          0           skip_connection6[0][0]           
                                                                 ffn_block7[0][0]                 
__________________________________________________________________________________________________
ffn_block8 (Sequential)         (None, 100)          21000       skip_connection7[0][0]           
__________________________________________________________________________________________________
skip_connection8 (Add)          (None, 100)          0           skip_connection7[0][0]           
                                                                 ffn_block8[0][0]                 
__________________________________________________________________________________________________
ffn_block9 (Sequential)         (None, 100)          21000       skip_connection8[0][0]           
__________________________________________________________________________________________________
skip_connection9 (Add)          (None, 100)          0           skip_connection8[0][0]           
                                                                 ffn_block9[0][0]                 
__________________________________________________________________________________________________
ffn_block10 (Sequential)        (None, 100)          21000       skip_connection9[0][0]           
__________________________________________________________________________________________________
skip_connection10 (Add)         (None, 100)          0           skip_connection9[0][0]           
                                                                 ffn_block10[0][0]                
__________________________________________________________________________________________________
ffn_block11 (Sequential)        (None, 100)          21000       skip_connection10[0][0]          
__________________________________________________________________________________________________
skip_connection11 (Add)         (None, 100)          0           skip_connection10[0][0]          
                                                                 ffn_block11[0][0]                
__________________________________________________________________________________________________
ffn_block12 (Sequential)        (None, 100)          21000       skip_connection11[0][0]          
__________________________________________________________________________________________________
skip_connection12 (Add)         (None, 100)          0           skip_connection11[0][0]          
                                                                 ffn_block12[0][0]                
__________________________________________________________________________________________________
ffn_block13 (Sequential)        (None, 100)          21000       skip_connection12[0][0]          
__________________________________________________________________________________________________
skip_connection13 (Add)         (None, 100)          0           skip_connection12[0][0]          
                                                                 ffn_block13[0][0]                
__________________________________________________________________________________________________
ffn_block14 (Sequential)        (None, 100)          21000       skip_connection13[0][0]          
__________________________________________________________________________________________________
skip_connection14 (Add)         (None, 100)          0           skip_connection13[0][0]          
                                                                 ffn_block14[0][0]                
__________________________________________________________________________________________________
ffn_block15 (Sequential)        (None, 100)          21000       skip_connection14[0][0]          
__________________________________________________________________________________________________
skip_connection15 (Add)         (None, 100)          0           skip_connection14[0][0]          
                                                                 ffn_block15[0][0]                
__________________________________________________________________________________________________
ffn_block16 (Sequential)        (None, 100)          21000       skip_connection15[0][0]          
__________________________________________________________________________________________________
skip_connection16 (Add)         (None, 100)          0           skip_connection15[0][0]          
                                                                 ffn_block16[0][0]                
__________________________________________________________________________________________________
ffn_block17 (Sequential)        (None, 100)          21000       skip_connection16[0][0]          
__________________________________________________________________________________________________
skip_connection17 (Add)         (None, 100)          0           skip_connection16[0][0]          
                                                                 ffn_block17[0][0]                
__________________________________________________________________________________________________
ffn_block18 (Sequential)        (None, 100)          21000       skip_connection17[0][0]          
__________________________________________________________________________________________________
skip_connection18 (Add)         (None, 100)          0           skip_connection17[0][0]          
                                                                 ffn_block18[0][0]                
__________________________________________________________________________________________________
ffn_block19 (Sequential)        (None, 100)          21000       skip_connection18[0][0]          
__________________________________________________________________________________________________
skip_connection19 (Add)         (None, 100)          0           skip_connection18[0][0]          
                                                                 ffn_block19[0][0]                
__________________________________________________________________________________________________
ffn_block20 (Sequential)        (None, 100)          21000       skip_connection19[0][0]          
__________________________________________________________________________________________________
skip_connection20 (Add)         (None, 100)          0           skip_connection19[0][0]          
                                                                 ffn_block20[0][0]                
__________________________________________________________________________________________________
ffn_block21 (Sequential)        (None, 100)          21000       skip_connection20[0][0]          
__________________________________________________________________________________________________
skip_connection21 (Add)         (None, 100)          0           skip_connection20[0][0]          
                                                                 ffn_block21[0][0]                
__________________________________________________________________________________________________
ffn_block22 (Sequential)        (None, 100)          21000       skip_connection21[0][0]          
__________________________________________________________________________________________________
skip_connection22 (Add)         (None, 100)          0           skip_connection21[0][0]          
                                                                 ffn_block22[0][0]                
__________________________________________________________________________________________________
ffn_block23 (Sequential)        (None, 100)          21000       skip_connection22[0][0]          
__________________________________________________________________________________________________
skip_connection23 (Add)         (None, 100)          0           skip_connection22[0][0]          
                                                                 ffn_block23[0][0]                
__________________________________________________________________________________________________
ffn_block24 (Sequential)        (None, 100)          21000       skip_connection23[0][0]          
__________________________________________________________________________________________________
skip_connection24 (Add)         (None, 100)          0           skip_connection23[0][0]          
                                                                 ffn_block24[0][0]                
__________________________________________________________________________________________________
ffn_block25 (Sequential)        (None, 100)          21000       skip_connection24[0][0]          
__________________________________________________________________________________________________
skip_connection25 (Add)         (None, 100)          0           skip_connection24[0][0]          
                                                                 ffn_block25[0][0]                
__________________________________________________________________________________________________
ffn_block26 (Sequential)        (None, 100)          21000       skip_connection25[0][0]          
__________________________________________________________________________________________________
skip_connection26 (Add)         (None, 100)          0           skip_connection25[0][0]          
                                                                 ffn_block26[0][0]                
__________________________________________________________________________________________________
ffn_block27 (Sequential)        (None, 100)          21000       skip_connection26[0][0]          
__________________________________________________________________________________________________
skip_connection27 (Add)         (None, 100)          0           skip_connection26[0][0]          
                                                                 ffn_block27[0][0]                
__________________________________________________________________________________________________
ffn_block28 (Sequential)        (None, 100)          21000       skip_connection27[0][0]          
__________________________________________________________________________________________________
skip_connection28 (Add)         (None, 100)          0           skip_connection27[0][0]          
                                                                 ffn_block28[0][0]                
__________________________________________________________________________________________________
ffn_block29 (Sequential)        (None, 100)          21000       skip_connection28[0][0]          
__________________________________________________________________________________________________
skip_connection29 (Add)         (None, 100)          0           skip_connection28[0][0]          
                                                                 ffn_block29[0][0]                
__________________________________________________________________________________________________
ffn_block30 (Sequential)        (None, 100)          21000       skip_connection29[0][0]          
__________________________________________________________________________________________________
skip_connection30 (Add)         (None, 100)          0           skip_connection29[0][0]          
                                                                 ffn_block30[0][0]                
__________________________________________________________________________________________________
ffn_block31 (Sequential)        (None, 100)          21000       skip_connection30[0][0]          
__________________________________________________________________________________________________
skip_connection31 (Add)         (None, 100)          0           skip_connection30[0][0]          
                                                                 ffn_block31[0][0]                
__________________________________________________________________________________________________
ffn_block32 (Sequential)        (None, 100)          21000       skip_connection31[0][0]          
__________________________________________________________________________________________________
skip_connection32 (Add)         (None, 100)          0           skip_connection31[0][0]          
                                                                 ffn_block32[0][0]                
__________________________________________________________________________________________________
ffn_block33 (Sequential)        (None, 100)          21000       skip_connection32[0][0]          
__________________________________________________________________________________________________
skip_connection33 (Add)         (None, 100)          0           skip_connection32[0][0]          
                                                                 ffn_block33[0][0]                
__________________________________________________________________________________________________
ffn_block34 (Sequential)        (None, 100)          21000       skip_connection33[0][0]          
__________________________________________________________________________________________________
skip_connection34 (Add)         (None, 100)          0           skip_connection33[0][0]          
                                                                 ffn_block34[0][0]                
__________________________________________________________________________________________________
ffn_block35 (Sequential)        (None, 100)          21000       skip_connection34[0][0]          
__________________________________________________________________________________________________
skip_connection35 (Add)         (None, 100)          0           skip_connection34[0][0]          
                                                                 ffn_block35[0][0]                
__________________________________________________________________________________________________
ffn_block36 (Sequential)        (None, 100)          21000       skip_connection35[0][0]          
__________________________________________________________________________________________________
skip_connection36 (Add)         (None, 100)          0           skip_connection35[0][0]          
                                                                 ffn_block36[0][0]                
__________________________________________________________________________________________________
ffn_block37 (Sequential)        (None, 100)          21000       skip_connection36[0][0]          
__________________________________________________________________________________________________
skip_connection37 (Add)         (None, 100)          0           skip_connection36[0][0]          
                                                                 ffn_block37[0][0]                
__________________________________________________________________________________________________
ffn_block38 (Sequential)        (None, 100)          21000       skip_connection37[0][0]          
__________________________________________________________________________________________________
skip_connection38 (Add)         (None, 100)          0           skip_connection37[0][0]          
                                                                 ffn_block38[0][0]                
__________________________________________________________________________________________________
ffn_block39 (Sequential)        (None, 100)          21000       skip_connection38[0][0]          
__________________________________________________________________________________________________
skip_connection39 (Add)         (None, 100)          0           skip_connection38[0][0]          
                                                                 ffn_block39[0][0]                
__________________________________________________________________________________________________
ffn_block40 (Sequential)        (None, 100)          21000       skip_connection39[0][0]          
__________________________________________________________________________________________________
skip_connection40 (Add)         (None, 100)          0           skip_connection39[0][0]          
                                                                 ffn_block40[0][0]                
__________________________________________________________________________________________________
ffn_block41 (Sequential)        (None, 100)          21000       skip_connection40[0][0]          
__________________________________________________________________________________________________
skip_connection41 (Add)         (None, 100)          0           skip_connection40[0][0]          
                                                                 ffn_block41[0][0]                
__________________________________________________________________________________________________
ffn_block42 (Sequential)        (None, 100)          21000       skip_connection41[0][0]          
__________________________________________________________________________________________________
skip_connection42 (Add)         (None, 100)          0           skip_connection41[0][0]          
                                                                 ffn_block42[0][0]                
__________________________________________________________________________________________________
ffn_block43 (Sequential)        (None, 100)          21000       skip_connection42[0][0]          
__________________________________________________________________________________________________
skip_connection43 (Add)         (None, 100)          0           skip_connection42[0][0]          
                                                                 ffn_block43[0][0]                
__________________________________________________________________________________________________
ffn_block44 (Sequential)        (None, 100)          21000       skip_connection43[0][0]          
__________________________________________________________________________________________________
skip_connection44 (Add)         (None, 100)          0           skip_connection43[0][0]          
                                                                 ffn_block44[0][0]                
__________________________________________________________________________________________________
ffn_block45 (Sequential)        (None, 100)          21000       skip_connection44[0][0]          
__________________________________________________________________________________________________
skip_connection45 (Add)         (None, 100)          0           skip_connection44[0][0]          
                                                                 ffn_block45[0][0]                
__________________________________________________________________________________________________
ffn_block46 (Sequential)        (None, 100)          21000       skip_connection45[0][0]          
__________________________________________________________________________________________________
skip_connection46 (Add)         (None, 100)          0           skip_connection45[0][0]          
                                                                 ffn_block46[0][0]                
__________________________________________________________________________________________________
ffn_block47 (Sequential)        (None, 100)          21000       skip_connection46[0][0]          
__________________________________________________________________________________________________
skip_connection47 (Add)         (None, 100)          0           skip_connection46[0][0]          
                                                                 ffn_block47[0][0]                
__________________________________________________________________________________________________
ffn_block48 (Sequential)        (None, 100)          21000       skip_connection47[0][0]          
__________________________________________________________________________________________________
skip_connection48 (Add)         (None, 100)          0           skip_connection47[0][0]          
                                                                 ffn_block48[0][0]                
__________________________________________________________________________________________________
ffn_block49 (Sequential)        (None, 100)          21000       skip_connection48[0][0]          
__________________________________________________________________________________________________
skip_connection49 (Add)         (None, 100)          0           skip_connection48[0][0]          
                                                                 ffn_block49[0][0]                
__________________________________________________________________________________________________
ffn_block50 (Sequential)        (None, 100)          21000       skip_connection49[0][0]          
__________________________________________________________________________________________________
skip_connection50 (Add)         (None, 100)          0           skip_connection49[0][0]          
                                                                 ffn_block50[0][0]                
__________________________________________________________________________________________________
ffn_block51 (Sequential)        (None, 100)          21000       skip_connection50[0][0]          
__________________________________________________________________________________________________
skip_connection51 (Add)         (None, 100)          0           skip_connection50[0][0]          
                                                                 ffn_block51[0][0]                
__________________________________________________________________________________________________
ffn_block52 (Sequential)        (None, 100)          21000       skip_connection51[0][0]          
__________________________________________________________________________________________________
skip_connection52 (Add)         (None, 100)          0           skip_connection51[0][0]          
                                                                 ffn_block52[0][0]                
__________________________________________________________________________________________________
ffn_block53 (Sequential)        (None, 100)          21000       skip_connection52[0][0]          
__________________________________________________________________________________________________
skip_connection53 (Add)         (None, 100)          0           skip_connection52[0][0]          
                                                                 ffn_block53[0][0]                
__________________________________________________________________________________________________
ffn_block54 (Sequential)        (None, 100)          21000       skip_connection53[0][0]          
__________________________________________________________________________________________________
skip_connection54 (Add)         (None, 100)          0           skip_connection53[0][0]          
                                                                 ffn_block54[0][0]                
__________________________________________________________________________________________________
ffn_block55 (Sequential)        (None, 100)          21000       skip_connection54[0][0]          
__________________________________________________________________________________________________
skip_connection55 (Add)         (None, 100)          0           skip_connection54[0][0]          
                                                                 ffn_block55[0][0]                
__________________________________________________________________________________________________
ffn_block56 (Sequential)        (None, 100)          21000       skip_connection55[0][0]          
__________________________________________________________________________________________________
skip_connection56 (Add)         (None, 100)          0           skip_connection55[0][0]          
                                                                 ffn_block56[0][0]                
__________________________________________________________________________________________________
ffn_block57 (Sequential)        (None, 100)          21000       skip_connection56[0][0]          
__________________________________________________________________________________________________
skip_connection57 (Add)         (None, 100)          0           skip_connection56[0][0]          
                                                                 ffn_block57[0][0]                
__________________________________________________________________________________________________
ffn_block58 (Sequential)        (None, 100)          21000       skip_connection57[0][0]          
__________________________________________________________________________________________________
skip_connection58 (Add)         (None, 100)          0           skip_connection57[0][0]          
                                                                 ffn_block58[0][0]                
__________________________________________________________________________________________________
ffn_block59 (Sequential)        (None, 100)          21000       skip_connection58[0][0]          
__________________________________________________________________________________________________
skip_connection59 (Add)         (None, 100)          0           skip_connection58[0][0]          
                                                                 ffn_block59[0][0]                
__________________________________________________________________________________________________
ffn_block60 (Sequential)        (None, 100)          21000       skip_connection59[0][0]          
__________________________________________________________________________________________________
skip_connection60 (Add)         (None, 100)          0           skip_connection59[0][0]          
                                                                 ffn_block60[0][0]                
__________________________________________________________________________________________________
ffn_block61 (Sequential)        (None, 100)          21000       skip_connection60[0][0]          
__________________________________________________________________________________________________
skip_connection61 (Add)         (None, 100)          0           skip_connection60[0][0]          
                                                                 ffn_block61[0][0]                
__________________________________________________________________________________________________
ffn_block62 (Sequential)        (None, 100)          21000       skip_connection61[0][0]          
__________________________________________________________________________________________________
skip_connection62 (Add)         (None, 100)          0           skip_connection61[0][0]          
                                                                 ffn_block62[0][0]                
__________________________________________________________________________________________________
ffn_block63 (Sequential)        (None, 100)          21000       skip_connection62[0][0]          
__________________________________________________________________________________________________
skip_connection63 (Add)         (None, 100)          0           skip_connection62[0][0]          
                                                                 ffn_block63[0][0]                
__________________________________________________________________________________________________
ffn_block64 (Sequential)        (None, 100)          21000       skip_connection63[0][0]          
__________________________________________________________________________________________________
skip_connection64 (Add)         (None, 100)          0           skip_connection63[0][0]          
                                                                 ffn_block64[0][0]                
__________________________________________________________________________________________________
ffn_block65 (Sequential)        (None, 100)          21000       skip_connection64[0][0]          
__________________________________________________________________________________________________
skip_connection65 (Add)         (None, 100)          0           skip_connection64[0][0]          
                                                                 ffn_block65[0][0]                
__________________________________________________________________________________________________
ffn_block66 (Sequential)        (None, 100)          21000       skip_connection65[0][0]          
__________________________________________________________________________________________________
skip_connection66 (Add)         (None, 100)          0           skip_connection65[0][0]          
                                                                 ffn_block66[0][0]                
__________________________________________________________________________________________________
ffn_block67 (Sequential)        (None, 100)          21000       skip_connection66[0][0]          
__________________________________________________________________________________________________
skip_connection67 (Add)         (None, 100)          0           skip_connection66[0][0]          
                                                                 ffn_block67[0][0]                
__________________________________________________________________________________________________
ffn_block68 (Sequential)        (None, 100)          21000       skip_connection67[0][0]          
__________________________________________________________________________________________________
skip_connection68 (Add)         (None, 100)          0           skip_connection67[0][0]          
                                                                 ffn_block68[0][0]                
__________________________________________________________________________________________________
ffn_block69 (Sequential)        (None, 100)          21000       skip_connection68[0][0]          
__________________________________________________________________________________________________
skip_connection69 (Add)         (None, 100)          0           skip_connection68[0][0]          
                                                                 ffn_block69[0][0]                
__________________________________________________________________________________________________
ffn_block70 (Sequential)        (None, 100)          21000       skip_connection69[0][0]          
__________________________________________________________________________________________________
skip_connection70 (Add)         (None, 100)          0           skip_connection69[0][0]          
                                                                 ffn_block70[0][0]                
__________________________________________________________________________________________________
ffn_block71 (Sequential)        (None, 100)          21000       skip_connection70[0][0]          
__________________________________________________________________________________________________
skip_connection71 (Add)         (None, 100)          0           skip_connection70[0][0]          
                                                                 ffn_block71[0][0]                
__________________________________________________________________________________________________
ffn_block72 (Sequential)        (None, 100)          21000       skip_connection71[0][0]          
__________________________________________________________________________________________________
skip_connection72 (Add)         (None, 100)          0           skip_connection71[0][0]          
                                                                 ffn_block72[0][0]                
__________________________________________________________________________________________________
ffn_block73 (Sequential)        (None, 100)          21000       skip_connection72[0][0]          
__________________________________________________________________________________________________
skip_connection73 (Add)         (None, 100)          0           skip_connection72[0][0]          
                                                                 ffn_block73[0][0]                
__________________________________________________________________________________________________
ffn_block74 (Sequential)        (None, 100)          21000       skip_connection73[0][0]          
__________________________________________________________________________________________________
skip_connection74 (Add)         (None, 100)          0           skip_connection73[0][0]          
                                                                 ffn_block74[0][0]                
__________________________________________________________________________________________________
ffn_block75 (Sequential)        (None, 100)          21000       skip_connection74[0][0]          
__________________________________________________________________________________________________
skip_connection75 (Add)         (None, 100)          0           skip_connection74[0][0]          
                                                                 ffn_block75[0][0]                
__________________________________________________________________________________________________
ffn_block76 (Sequential)        (None, 100)          21000       skip_connection75[0][0]          
__________________________________________________________________________________________________
skip_connection76 (Add)         (None, 100)          0           skip_connection75[0][0]          
                                                                 ffn_block76[0][0]                
__________________________________________________________________________________________________
ffn_block77 (Sequential)        (None, 100)          21000       skip_connection76[0][0]          
__________________________________________________________________________________________________
skip_connection77 (Add)         (None, 100)          0           skip_connection76[0][0]          
                                                                 ffn_block77[0][0]                
__________________________________________________________________________________________________
ffn_block78 (Sequential)        (None, 100)          21000       skip_connection77[0][0]          
__________________________________________________________________________________________________
skip_connection78 (Add)         (None, 100)          0           skip_connection77[0][0]          
                                                                 ffn_block78[0][0]                
__________________________________________________________________________________________________
ffn_block79 (Sequential)        (None, 100)          21000       skip_connection78[0][0]          
__________________________________________________________________________________________________
skip_connection79 (Add)         (None, 100)          0           skip_connection78[0][0]          
                                                                 ffn_block79[0][0]                
__________________________________________________________________________________________________
ffn_block80 (Sequential)        (None, 100)          21000       skip_connection79[0][0]          
__________________________________________________________________________________________________
skip_connection80 (Add)         (None, 100)          0           skip_connection79[0][0]          
                                                                 ffn_block80[0][0]                
__________________________________________________________________________________________________
ffn_block81 (Sequential)        (None, 100)          21000       skip_connection80[0][0]          
__________________________________________________________________________________________________
skip_connection81 (Add)         (None, 100)          0           skip_connection80[0][0]          
                                                                 ffn_block81[0][0]                
__________________________________________________________________________________________________
ffn_block82 (Sequential)        (None, 100)          21000       skip_connection81[0][0]          
__________________________________________________________________________________________________
skip_connection82 (Add)         (None, 100)          0           skip_connection81[0][0]          
                                                                 ffn_block82[0][0]                
__________________________________________________________________________________________________
ffn_block83 (Sequential)        (None, 100)          21000       skip_connection82[0][0]          
__________________________________________________________________________________________________
skip_connection83 (Add)         (None, 100)          0           skip_connection82[0][0]          
                                                                 ffn_block83[0][0]                
__________________________________________________________________________________________________
ffn_block84 (Sequential)        (None, 100)          21000       skip_connection83[0][0]          
__________________________________________________________________________________________________
skip_connection84 (Add)         (None, 100)          0           skip_connection83[0][0]          
                                                                 ffn_block84[0][0]                
__________________________________________________________________________________________________
ffn_block85 (Sequential)        (None, 100)          21000       skip_connection84[0][0]          
__________________________________________________________________________________________________
skip_connection85 (Add)         (None, 100)          0           skip_connection84[0][0]          
                                                                 ffn_block85[0][0]                
__________________________________________________________________________________________________
ffn_block86 (Sequential)        (None, 100)          21000       skip_connection85[0][0]          
__________________________________________________________________________________________________
skip_connection86 (Add)         (None, 100)          0           skip_connection85[0][0]          
                                                                 ffn_block86[0][0]                
__________________________________________________________________________________________________
ffn_block87 (Sequential)        (None, 100)          21000       skip_connection86[0][0]          
__________________________________________________________________________________________________
skip_connection87 (Add)         (None, 100)          0           skip_connection86[0][0]          
                                                                 ffn_block87[0][0]                
__________________________________________________________________________________________________
ffn_block88 (Sequential)        (None, 100)          21000       skip_connection87[0][0]          
__________________________________________________________________________________________________
skip_connection88 (Add)         (None, 100)          0           skip_connection87[0][0]          
                                                                 ffn_block88[0][0]                
__________________________________________________________________________________________________
ffn_block89 (Sequential)        (None, 100)          21000       skip_connection88[0][0]          
__________________________________________________________________________________________________
skip_connection89 (Add)         (None, 100)          0           skip_connection88[0][0]          
                                                                 ffn_block89[0][0]                
__________________________________________________________________________________________________
ffn_block90 (Sequential)        (None, 100)          21000       skip_connection89[0][0]          
__________________________________________________________________________________________________
skip_connection90 (Add)         (None, 100)          0           skip_connection89[0][0]          
                                                                 ffn_block90[0][0]                
__________________________________________________________________________________________________
ffn_block91 (Sequential)        (None, 100)          21000       skip_connection90[0][0]          
__________________________________________________________________________________________________
skip_connection91 (Add)         (None, 100)          0           skip_connection90[0][0]          
                                                                 ffn_block91[0][0]                
__________________________________________________________________________________________________
ffn_block92 (Sequential)        (None, 100)          21000       skip_connection91[0][0]          
__________________________________________________________________________________________________
skip_connection92 (Add)         (None, 100)          0           skip_connection91[0][0]          
                                                                 ffn_block92[0][0]                
__________________________________________________________________________________________________
ffn_block93 (Sequential)        (None, 100)          21000       skip_connection92[0][0]          
__________________________________________________________________________________________________
skip_connection93 (Add)         (None, 100)          0           skip_connection92[0][0]          
                                                                 ffn_block93[0][0]                
__________________________________________________________________________________________________
ffn_block94 (Sequential)        (None, 100)          21000       skip_connection93[0][0]          
__________________________________________________________________________________________________
skip_connection94 (Add)         (None, 100)          0           skip_connection93[0][0]          
                                                                 ffn_block94[0][0]                
__________________________________________________________________________________________________
ffn_block95 (Sequential)        (None, 100)          21000       skip_connection94[0][0]          
__________________________________________________________________________________________________
skip_connection95 (Add)         (None, 100)          0           skip_connection94[0][0]          
                                                                 ffn_block95[0][0]                
__________________________________________________________________________________________________
ffn_block96 (Sequential)        (None, 100)          21000       skip_connection95[0][0]          
__________________________________________________________________________________________________
skip_connection96 (Add)         (None, 100)          0           skip_connection95[0][0]          
                                                                 ffn_block96[0][0]                
__________________________________________________________________________________________________
ffn_block97 (Sequential)        (None, 100)          21000       skip_connection96[0][0]          
__________________________________________________________________________________________________
skip_connection97 (Add)         (None, 100)          0           skip_connection96[0][0]          
                                                                 ffn_block97[0][0]                
__________________________________________________________________________________________________
ffn_block98 (Sequential)        (None, 100)          21000       skip_connection97[0][0]          
__________________________________________________________________________________________________
skip_connection98 (Add)         (None, 100)          0           skip_connection97[0][0]          
                                                                 ffn_block98[0][0]                
__________________________________________________________________________________________________
ffn_block99 (Sequential)        (None, 100)          21000       skip_connection98[0][0]          
__________________________________________________________________________________________________
skip_connection99 (Add)         (None, 100)          0           skip_connection98[0][0]          
                                                                 ffn_block99[0][0]                
__________________________________________________________________________________________________
ffn_block100 (Sequential)       (None, 100)          21000       skip_connection99[0][0]          
__________________________________________________________________________________________________
skip_connection100 (Add)        (None, 100)          0           skip_connection99[0][0]          
                                                                 ffn_block100[0][0]               
__________________________________________________________________________________________________
ffn_block101 (Sequential)       (None, 100)          21000       skip_connection100[0][0]         
__________________________________________________________________________________________________
skip_connection101 (Add)        (None, 100)          0           skip_connection100[0][0]         
                                                                 ffn_block101[0][0]               
__________________________________________________________________________________________________
logits (Dense)                  (None, 5)            505         skip_connection101[0][0]         
==================================================================================================
Total params: 2,114,121
Trainable params: 2,073,863
Non-trainable params: 40,258
__________________________________________________________________________________________________


history = run_experiment(baseline_model, X_train, y_train.argmax(axis=1))

Epoch 1/500
225/225 [==============================] - 18s 78ms/step - loss: 1.6313 - acc: 0.9280 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 2/500
225/225 [==============================] - 15s 67ms/step - loss: 0.3008 - acc: 0.9685 - val_loss: 5.2452e-10 - val_acc: 1.0000
Epoch 3/500
225/225 [==============================] - 14s 62ms/step - loss: 0.1911 - acc: 0.9738 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 4/500
225/225 [==============================] - 14s 64ms/step - loss: 0.1734 - acc: 0.9757 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 5/500
225/225 [==============================] - 15s 68ms/step - loss: 0.1564 - acc: 0.9776 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 6/500
225/225 [==============================] - 15s 67ms/step - loss: 0.1117 - acc: 0.9783 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 7/500
225/225 [==============================] - 14s 64ms/step - loss: 0.1038 - acc: 0.9798 - val_loss: 1.0888e-08 - val_acc: 1.0000
Epoch 8/500
225/225 [==============================] - 15s 65ms/step - loss: 0.0575 - acc: 0.9845 - val_loss: 3.7503e-07 - val_acc: 1.0000
Epoch 9/500
225/225 [==============================] - 15s 66ms/step - loss: 0.0683 - acc: 0.9846 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 10/500
225/225 [==============================] - 16s 71ms/step - loss: 0.0810 - acc: 0.9825 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 11/500
225/225 [==============================] - 15s 67ms/step - loss: 0.0821 - acc: 0.9828 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 12/500
225/225 [==============================] - 16s 69ms/step - loss: 0.0636 - acc: 0.9843 - val_loss: 4.3360e-08 - val_acc: 1.0000
Epoch 13/500
225/225 [==============================] - 16s 70ms/step - loss: 0.0493 - acc: 0.9862 - val_loss: 0.0000e+00 - val_acc: 1.0000
Epoch 14/500
225/225 [==============================] - 47s 209ms/step - loss: 0.0451 - acc: 0.9862 - val_loss: 1.0017e-04 - val_acc: 1.0000
Epoch 15/500
 67/225 [=======>......................] - ETA: 36s - loss: 0.0629 - acc: 0.9852


display_learning_curves(history)


_, test_accuracy = baseline_model.evaluate(x=X_test, y=y_test.argmax(axis=1), verbose=0)
print(f"Test accuracy: {round(test_accuracy * 100, 2)}%")

Example of prediction DAST score's class in different method to study and interpretation the features effect on DAST.¶

DAST¶

case (1):¶

DAST¶

1) Decision Tree¶

GINI¶

Entropy¶

Pruned¶

2) Random Forest¶

GINI¶

Entropy¶

Pruned¶

3) Gradient Boosting Classifier¶

Pruned¶

4) Gaussian Naive Bayes¶

5) SVM¶

6) Neural Network¶

7) Lightgbm Model Parameters and Training¶

very important note for tree methods¶

8) XGBoost¶

9) convolutional neural network 1D¶

with/ without standardize the data¶

Number of Filters¶

Size of Kernel¶

Multi-Headed Convolutional Neural Network¶

10) Graph neural network¶

	DAST	SEX	HISPANIC	RACE	VET	ACTIVE	DEPLOY	AUDIT	COSCREEN	BI	...	BINGEDAYS	DRUGDAYS	ALCDRUGS	DAYSCOCAINE	MARYJDAYS	ANYOPIATEDAYS	METHDAYS	INJECT	AGE	TOBMONTH
3	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	1.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	24.0	1.0
4	0.0	0.0	0.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0	...	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	54.0	1.0
5	1.0	1.0	0.0	2.0	0.0	0.0	0.0	1.0	0.0	1.0	...	5.0	20.0	10.0	0.0	20.0	0.0	0.0	0.0	27.0	1.0
6	2.0	1.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	...	0.0	30.0	0.0	0.0	0.0	0.0	30.0	0.0	37.0	1.0
8	2.0	0.0	0.0	3.0	1.0	1.0	4.0	0.0	0.0	0.0	...	0.0	14.0	0.0	3.0	5.0	0.0	0.0	0.0	31.0	1.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
6279	0.0	1.0	0.0	2.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	49.0	1.0
6280	0.0	1.0	0.0	2.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	57.0	1.0
6286	0.0	1.0	0.0	2.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	20.0	0.0
6288	1.0	0.0	0.0	2.0	0.0	0.0	0.0	0.0	0.0	1.0	...	0.0	2.0	0.0	0.0	2.0	0.0	0.0	0.0	24.0	1.0
6289	4.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	1.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	35.0	0.0

	Importance
Feature
26	0.021133
24	0.016833
25	0.003667
23	0.002600
22	0.001867
28	0.000800
2	0.000267
10	0.000233
8	0.000133
12	0.000100
17	0.000000
27	0.000000
21	0.000000
20	0.000000
19	0.000000
18	0.000000
0	0.000000
16	0.000000
15	0.000000
1	0.000000
13	0.000000
11	0.000000
9	0.000000
7	0.000000
6	0.000000
5	0.000000
4	0.000000
3	0.000000
14	0.000000

Feature	Value
BI_1	0.00
AUDIT_2	0.00
DEPLOY_2	0.00
AUDIT_1	0.00
DEPLOY_1	0.00
ALCDRUGS	0.00
RT_1	0.00
METHDAYS	0.09
DEPLOY_4	0.00
ACTIVE_1	0.00
RACE_3	0.00
RACE_2	0.00
SEX_2	0.00
COSCREEN_1	1.00
ANYALC	0.00
ANYOPIATEDAYS	0.00
INJECT_1	1.00
DEPLOY_3	0.00
MARYJDAYS	0.00
BT_1	0.00
DAYSCOCAINE	0.00
DAST	0.00
VET_1	0.00
AGE	0.00
HISPANIC_1	1.00